CMBEBIH 2017

This research implements a feed forward back propagation network (FFBPN) for classification of breast cancer cases to malignant or benign. The purpose of the research is to design an Artificial Neural Network (ANN) with high and acceptable level of accuracy by selecting the number of hidden layers, number of neurons in the hidden layer and the type of activation functions in hidden layers. Samples for training and validation of ANN are obtained from Wisconsin Breast Cancer Database (WBCD) which is open access dataset. The dataset contains 699 samples that were distributed to two groups: 599 samples in training setand 100 samples in testing set. Each sample has 9 attributes representing 9 characteristics of breast fine-needle aspirates (FNAs) as inputs of the network. This experiment includes a comparison among the obtained mean square error (MSE) when using three transfer functions: LOGSIG, TANSIG, and PURELINE in neural network architetcures.Impact of different number of layers (1, 2, and 3 layers were used)in ANN architectureon output accuracy was also investigated. Also, this research provides the results of ANN performance for different number of neurons in hidden layer (20, 21, 22, 23, 24 neurons were implemented). The results show that the best network design is that one with three hidden layers, 21 neurons in the hidden layer, and TANSIG as activation function.

The aim of this work is to present an architectural overview of a novel web platform used for heterogeneous biomedical time series analysis. Its architecture is based on three subprojects: frontend, backend, and processing. Frontend uses several contemporary web technologies to present a fast, responsive and pleasing user interface. Backend, written in Java, communicates with a database and with other servers, on which the processing subproject is deployed. The processing subproject contains several frameworks intended for: record input handling, signal preprocessing, data visualization, general time series features extraction, specific time series features extraction (e.g. heart rate variability and electroencephalogram), data mining, and reporting. The platform is in an early phase of implementation, but we demonstrate its features and capabilities, of which feature extraction frameworks and signal visualization currently stand out.

Monitoring of heart rate variability that could reflect autonomic nervous system tone might be of clinical importance in subjects who are scheduled for elective surgical treatment.Individuals with balanced autonomic nervous system tone in the situations of increased demands and stress load have been shown to have preserved hemodynamic reserve which is very important for hemodynamic stability. On the contrary, individuals who had developed some alterations of autonomic nervous tone as a result of different physiological changes have shown predisposition to inadequate hemodynamic adaptability to different stressful conditions and surgical procedure as a possible major stressful event.The aim of the trial was to estimate the parameters of heart rate variability in time and frequency domain for subjects scheduled for elective surgical procedures. Thirty-six subjects were allocated to two groups. Individuals who had developed mild hypertension were allocated to first group while normotensive individuals constituted the second group. Recordings of electrocardiogram were analyzed in time domain : SDNN (standard deviation of NN intervals), RMSSD (root mean square of the successive differences), and in frequency domain: power of the total spectrum of heart rate variability(TP),power of low frequency band (LF, range 0,04-0,15Hz), power of high frequency range(HF, range 0,15-0,4 Hz). Analysis of the values of hemodynamic parameters has shown different hemodynamic parameters but no significant statistical differences were found between the groups. Analysis of the values of time-domain and frequency-domain parameters of heart rate variability has shown variations of the SDNN, RMSSD and parameters of total spectrum power and LF and HF spectra while no statistically significant difference was found. The results have shown variations of time-domain and frequency-domain parameters of heart rate variability in individuals with mild hypertension and normotensive individuals, but for this specific groups of patients there was no statistically significant difference.

Blood pulse waveform relates to the physical properties of the circulatory system, and carries valuable hemodynamic information for the management of cardiovascular patients. In this paper, we present a modeling technique to reconstruct and characterize the cardiac-related pulse waves, observed in laser Doppler flowmetry signals of the peripheral skin perfusion. We tested the sensitivity of the proposed model to physiological alterations of the vascular system, investigating the effect of ageing on a set of parameters describing the reconstructed pulse waves. Waveform data collected from a set of 56 subjects demonstrate the existence of a significant correlation between ageing and the shape of the peripheral perfusion pulse waves, and indicate a possible relationship with the mechanical properties of the vascular tree.

In this study, different data mining techniques has been used for classification of healthy controls and patients diagnosed by First Episode Psychosis with respect to complexity of frequency band activities (Delta, Theta, Alpha, Beta, Gamma)in multi channel EEG measurements mediated by emotional, static and visual stimuli including affective pictures from IAPS. Degree of local EEG complexity has been correlated by largeness of the dominant principle component in each EEG sub-band. The best classification performances are provided by Rotation Forest, Simple Logistic and Artificial Neural Networks when the components from occipito-parietal and posterio-temporal locations (P3, P4, O1, O2, T5 and T6) are considered as features in Gamma with respect to neutral emotional state.

Multiple sclerosis (MS) causes severe gait problems and there are limited studies to quantitatively identify the specific gait parameters that are affected. The aim of the current study was to characterize the temporal gait parameters in MS patients and ascribe them to clinical variables, in order to enable target-oriented management. A total of 14 MS patients and 11 healthy controls (CO) were evaluated clinically by expanded disability status scale (EDSS) and quantitatively by the Timed 25 Foot Walk (T25FW) using non-invasive wireless inertial sensors. The self-selected walking velocity was used as a covariate in the analysis to ensure that group differences were not due to differences in walking velocity between the MS and CO groups. Reduced step time and cadence were seen in patients with MS. We also found significant correlations between biomechanical gait parameters and EDSS score, which provides a clinical rating of disease severity. Temporal gait variability noted as associated to slower walk in MS.

Medical image denoising is an important and one of the most challenging fields of biomedical image processing. The presence of noise reduces the visual quality of medical images and impairs the ability to perform accurate diagnosis and treatment. The principal aim of denoising is to improve the perceived quality of images, remove the undesired noise, while preserving the diagnostically relevant information. This paper proposes an adaptive scheme for denoising of X-ray medical images. The proposed method adopts the use of multiple multilayer perceptrons to perform image denoising. Each multilayer perceptron is trained to perform image denoising at a specific noise level. The proposed method relies on the singular value decomposition of images to estimate the level of additive white Gaussian noise that is present in images. In an attempt to optimize the performance of the proposed method, the paper investigates how the choice of image segmentation block size and various options for the multilayer perceptron architecture affect the ability of artificial neural networks to perform image denoising at various noise levels. The performances of the proposed image denoising method is evaluated on a database X-ray images. The experimental results demonstrate that compared to a single MLP based approach to image denoising, the proposed image denoising scheme improves and provides a more consistent image denoising performance across noise levels.

Development of an accurate skin permeability model is becoming increasingly important as skin has been more utilized in recent development of drug delivery methods. This paper presents results of development of Artificial Neural Network (ANN) for prediction of skin permeability. The performance of developed ANN was compared to three regression algorithms used in this paper. The prediction of skin permeability is based on three input parameters: molecular weight, partition coefficient - log(P), and melting temperature for each drug. The dataset of 400 samples was used for prediction of skin permeability. Out of that number, 75% was used for training of ANN, and testing of developed ANN was performed on 100 samples from the dataset. During testing, system correctly predicted 76.7%. This dataset was also used as input to three ensemble techniques based on decision trees: REPTree, Bagging, RandomSubSpaceDeveloped. It was shown that Bagging algorithm outperformed developed ANN with 81% while RandomSubspace performed at 73.3%. System can be used in laboratory conditions and can be used in the future for drug discovery.

Abnormal and uncontrolled cell divisions cause brain tumors. Fast and accurate detection of tumors in early phase is important for succesfull diagnosis and treatment. Expert physicians use image slices obtained from advanced imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomopghraphy (CT) to define existing of a tumor. This process has a difficulty as it requires a high concentration on many image slices. On the other hand, image processing techniques can successfully be used to detect a tumor and its sizes in order to assist to expert physicians. In this work, brain tumor detection and volume estimation by using FLAIR, T1 Pre Gadolinium and T1 Post Gadolinium (T1C) MRI protocols is presented. Method used in this study is fully automatic and applicable to different types of tumors. The work has been tested on 500 visual DICOM format axial brain MR slices of ten patients. Tumor detection is realized by using left-right symmetry analysis assuming that brain consists of two symmetric cerebral hemispheres. Also, thresholding, skull stripping and fuzzy c mean clustering techniques are applied to detect abnormal brain regions. Tumor volume is calculated by the help of detected tumor area of each MRI slice and MRI slice thickness information obtained from DICOM header.

High resolution digital medical images are stored in DICOM (Digital Imaging and Communications in Medicine) format that requires high storage space in database. Therefore reducing the image size while maintaining diagnostic quality can increase the memory usage efficiency in PACS. In this study, diagnostic regions of interest (ROI) of pelvis radiographs marked by the radiologist are segmented and adaptively compressed by using image processing algorithms. There are three ROIs marked by red, blue and green in every image. ROI contoured by red is defined as the most significant region in the image and compressed by lossless JPEG algorithm. Blue and green regions have less importance than the red region but still contain diagnostic data compared to the rest of the image. Therefore, these regions are compressed by lossy JPEG algorithm with higher quality factor than rest of the image. Non-contoured region is compressed by low quality factor which does not have any diagnostic information about the patient. Several compression ratios are used to determine sufficient quality and appropriate compression level. Compression ratio (CR), peak signal to noise ratio (PSNR), bits per pixel (BPP) and signal to noise ratio (SNR) values are calculated for objective evaluation of image quality. Experimental results show that original images can approximately be compressed six times without losing any diagnostic data. In pelvis radiographs marking multiple regions of interest and adaptive compression of more than one ROI is a new approach. It is believed that this method will improve database management efficiency of PACS while preserving diagnostic image content.

The brain arteriovenous malformation (AVM) is an abnormal connection between arteries and veins of the brain, bypassing the capillary system. Endovascular embolization was performed in thirty-two patients with cerebral AVMs.The objective of endovascular AVM treatment is set for each patient upon consultations with a radiologist and a neurosurgeon. In most cases, the disorder is asymptomatic. We report our initial experiences in the treatment of brain AVMs with Onyx embolization.Methods Between January 2015 and December 2015, 32 patients with brain AVMs were embolized with Onyx. Clinical presentation included incidental finding in 2 patients, neurologic deficits in 1 patient, headaches in 7 patients, seizures in 9 patients and intracerebral haemorrhage in 12 patients. According to the Spetzler–Martin scale, one AVMs was grade I, 5 were grade II, 17 were grade III, 7 were grade IV, and 2 were grade V. Twenty-eight (86%) AVMs were located in eloquent regions.Initial complete obliteration after final embolization was achieved in 7 patients (20.2%), with an average of 85.5% (range, 30-100%) volume reduction. One- year follow-up angiography was performed on 11 (34.8%) patients.Conclusions Endovascular treatment of cerebral AVMs with super selective embolization with ONYX is a safe and effective alternative treatment paths next to microsurgery.

The utilization of optical imaging for the analysis and modeling of microcirculatory flow patterns is raising significant interest. This work focuses on the analysis of the alterations in the spatial distribution of blood flow caused by exposing the skin at a variable temperature. In optical imaging, the measurement of local perfusion at pixel level is not reliable because of the very low signal to noise ratio (SNR) of the resulting signal. To cope with this limitation, a reference signal of pulsatile blood flow is computed by averaging a large region of skin, thus obtaining an improved SNR. Then, for each pixel, we estimate the time shift between the local blood pulse wave and the reference signal, evaluating the peak of the correlation function between the two signals. An image representing the spatial distribution of the time delay is thus created.Textural parameters derived from cooccurrence matrices and from fractal analysis show that both skin heating and cooling produce alterations of the spatial distribution of blood perfusion.

Hip osteoarthritis (OA) can be highly disabling and eventually may necessitate total replacement of the joint. Studies with computer-based analysis of the hip OA may give new insight both in imaging and clinical evaluation of the disease. In this study, new acetabular angle measurement methods of femoral head-neck-shaft angle (CCD), center-edge angle (CE) and acetabular depth-to-width ratio (ADR) are reconstructed via a computer based analysis technique for robust detection of OA on anteroposterior (AP) hip radiographs. The evaluation and validation of this computer-assisted system is performed by comparing these new automated methods with those of traditional manual measurement methods done by one orthopaedist and one radiologist. The 50 adult hip AP radiographs with OA are used and overall measurements are produced for both sides of the hip on radiographs separately. The mean average difference between these two measurement methods for CCD angle is found 1°±1,2°, for CE angle 1°±1,5° and for ADR ratio 1±1,4 respectively. The results show that this new automated angle and ratio measurement system can be found feasible and user friendly by clinicians owing to the similarity between the comparative results of two measurement methods statistically.

Objective: Sexual dimorphism manifests in all bodily structures, including bones, and as such is used to determine sex of skeletal remains. Two methodological approaches are used in skeletal sex determination - osteoscopic and osteometric. Our objectives were to determine the prediction (effectiveness) of sex determination based on observed craniometric (linear) diameters of the skulls and determine the most frequent and the least frequent craniometric (linear) skull diameters in our tested sample. Using the multivariate binary logistic regression, we tested the effect of craniometric (linear) diameters on sexual dimorphism in skulls.Methods and material: Our study was conducted on 211 macerated and degreased human skulls on which we measured seven linear diameters of the skull: L1, maximum cranial length, glabella-opisthion; L2, maximum cranial width, porion-porion; L3, maximum cranial height, vertex-porion; L4, maximum viscerocranium width, zygion-zygion; L5, upper face height, nasion-prosthion; L6, nasion-basion; L7, basion-prosthion.Results: Univariately, all seven observed craniometric (linear) skull diameters showed statistically significant effect on sex determination. Multivariately, statistical significance in sex determination was shown by three linear diameters: L2 (porion-porion), L4 (zygion-zygion) and L5 (nasion-prosthion), therefore, for sex determination of our sample population, we proposed the “L” model using these diameters.Conclusion: Growth of all seven linear diameters growing probability that the skull is classified as the skull of the male sex . Univariately and multivariately, linear diameter L4 (zygon-zygon) proved to be most effective in sex determination. The accuracy of sex determination in male skulls from our sample using the “L” model is 85%, while the accuracy of sex determination in female skulls is much lower and is 68%.

Eustachian Tube Dysfunction (ETD) is an ailment many people suffer, yet the exact cause of the problem is a subject for research. A tympanic cavity air exchange sensor is designed and used for monitoring the air exchange during operation of the Eustachian tube. Observation of EMG activity of muscles together with the observation of air exchange activity of Eustachian Tube while the Eustachian Tube opens, have revealed important information about the state of Eustachian Tube and the ETD problem. Early results suggest the possibility of a new way of identifying deteriorating status of the Eustachian Tube before it becomes totally dysfunctional and even classifying ETD dysfunction levels according to the output provided by the Tympanic Cavity Air Exchange sensor. This paper intends to provide the design details of the air exchange sensor used in the experiments and explain how the sensor was used to get information about the state of Eustachian Tube Dysfunction problem.

Nerve cuff electrodes provide a safe technique for recording nerve signals. A four-contact cuff electrode was modelled and used to evaluate selective recording from peripheral nerve. Fitzhugh-Nagumo equations were used to model the electromagnetic fields generated by active nerves and electrodes. The selectivity was increased with increasing the distance between active sources and increasing the number of contacts. Programmable System on Chip (PSoC) was used to implement and test proposed structure. Using the proper and low noise preamplifier and filter block we could record noiseless signals from sciatic nerve of a rat. The results of this study showed that Fitzhugh-Nagumo equations could model the nerve excitation accurately and be used in computer simulation for study nervous system. Also indicated that multicontact cuff electrode could be used in recording peripheral nerve signals to discriminate active fascicles in a nerve bundle.

The methodology, technology of fabrication and testing a multi-electrode spiral cuff for selective activation of fibres in particular superficial regions of a peripheral nerve is presented.Stimulating electrodes were made of 0.03-mm-thick platinum foil strips with 99.99 wt.% purity. Optimum conditions for welding the stainless steel wire with the platinum foil and to reveal the microstructure of the welds were defined using the scanning electron microscopy. The electrochemical performance of platinum electrodes within a multi-electrode spiral cuff was investigated “in vitro” while stimulating performance was tested “in vivo”.The fabricated cuff consists of 33 electrodes organised in eleven longitudinal groups of three electrodes. The total cuff length is 17 mm and internal diameter is 2.5mm to fit the size of the human cervical vagus nerve.Results show that welds do not show any welding defects. The results of “in vitro” testing showed that potentials across the electrode-electrolyte interface did not exceed the safe potential limits for water electrolysis. The observed effects of “in vivo” testing with a stimuli train via triplet of electrodes 1 and current intensity i _c =2.5 mA, modified selectively autonomic control of the SA and/or AV node.

Typical EMG measurement system consists of one central device with several channels; which are connected to the central unit with wires. Central device samples data from channels and supplies energy for the channels. It transfers data further to a device providing the user with graphical interface. Connection from central device to user interface device can be with or without wires. Very common drawback of such systems is that the wires limit patient movements; make EMG measurements relatively uncomfortable and they are not available for personal use because of relatively high prices.The goal of this project was to design, construct and test a compact-size, wireless and surface-electrode EMG measurement system. The intention is that device could be used as a single channel wireless EMG acquisition system which uses smartphone as a graphical user interface. Due to its simplicity and low price it is hoped to be available for home, everyday, personal use.

Magnetic Resonance Imaging (MRI) is a promising candidate compare to X-Ray fluoroscopy for interventional cardiovascular procedures due to its ionizing radiation free mechanism and superior soft tissue contrast. However, Interventional MRI field lacks dedicated clinical grade MRI safe and visible devices. In this study, we designed and developed a Computer Numerical Control (CNC) based thin film conductive ink printing system for developing low profile “active” interventional devices for cardiovascular procedures under MRI. The proposed automated system allows forming three-dimensional receiver antenna configurations automatically onto non-planar surfaces. The developed system decreased the process time and increased reproducibility significantly compared to alternative lithography-based techniques also used for low profile active device development. The validation and calibration test results showed that the motion control system worked within a tolerance of 2 μm and the dispenser unit had more than 90% accuracy. As a part of this study, a loop RF antenna was designed and formed on an MRI-compatible needle using biocompatible heat shrink polymer. MRI visibility and RF induced heating tests were performed successfully for the prototype active needle. An identical active needle was fabricated using conventional methods to compare the overall device profile and MRI visibility performance.

Experimental verification of the simulation model for modified digital stochastic measurement (MDSM) of biomedical signals in the time domain, is presented in this paper. This method is based on well-known digital stochastic measurement method (DSMM) with low-resolution analog-to-digital converters (ADCs) and accumulation. An electrooculography (EOG) signal is used as an example of a real low nonstationary biomedical signal. Realized experimental model is based on a personal computer (PC) with additional microcontroller hardware for analogue signal processing. The experimental printed circuit board (PCB) has been designed with microcontroller (MCU) STM32F303C6T6. The experimental results are compared with the results of simulations, and the comparison confirms the simulation. Considering obtained results, the suggested model can be used for design and realization of an instrument with sufficient accuracy, benefiting from the hardware simplicity of the method.

The usage of Artificial Neural Networks (ANN) for the prediction of water pollution has been investigated more extensively over the past few years, and the reason is due to the ANNs efficiency at approximating complex functions. One particular way of designing an ANN used for treatment of water is to use the characteristics of the waste and pollution sources as inputs (water parameters) and to use the appearance of pollutants as ANN outputs. This way, the designed ANNs are able to determine the waste load from different sources of water environments. This paper presents the design and testing of a feedforward neural network for the prediction of photo-degradation in suspension of manganese doped zinc-oxide nanoparticles under visible-light irradiation. The developed ANN was trained and validated using 210 samples by means of the Levenberg–Marquardt algorithm. The accuracy of true predictions, based on the testing dataset, was 93.78%. The developed system proved to be robust and simple for the prediction of photo-degradation, and can be implemented for the development of systems used for educational purposes.

Protein-nanoparticle conjugation provides unique interactions be-tween biological systems and synthetic materials used for analytical, diagnostic and therapeutic applications. This paper presents the development of Artificial Neural Network (ANN) for quantification of proteins concentration adsorbed on gold nanoparticles (Au NPs). Single hidden layer feedforward ANN is based on concentration of free proteins as input parameters, while concentration of con-jugated proteins is desired output. Totally, 210 samples were used, 200 of them derived from experiment and 10 additionally added as blank samples. Training data sets contain 120 samples, out of which 108 samples are used for estimation and 12 for validation. The ANN system is subsequently validated with 90 sam-ples, 80 samples from experiment and 10 additionally added. From 80 of sam-ples with known protein concentration, 74 are successfully quantified as pro-teins adsorbed on nanoparticles, which gives sensitivity of 92.5%. Out of exper-iment data, 10 blank samples are correctly classified as free of proteins giving the specificity of 100%. Developed system can be used in laboratory conditions and further validated on new experimental samples.

This paper presents microfluidic device, constructed from polydimethylsiloxane and glass, which is designed to perform on-chip micro-titration of biological solutions. The chip is composed of several mixing micro-channels that measures 100×100µm2 in extent and that automatically dilute an oxidizing agent in order to determine the amount of reducing agent present in biological solution. Concept of the diffusion as a dominant process for fluid mixing and achieving gradient of dilution, is analysed and reviewed. Types of biological samples, length of the mixing channel, input flow rate and applied pressure are discussed as main design parameters. Experimental results of utilizing the chip in microtitration studies are presented.

This paper presents a review on available researches, when it comes to the usage of quantum dots in detection and treatment of the most common form of dementia, and that is Alzheimer’s disease (AD). Quantum dots (QDs), as an essential material of nanotechnology, give unique approaches and solutions for preventing and curing AD. In this paper, CdSe/ZnS quantum dots and their application features are analyzed and proposed as the possible solution for inhibition of events in the organism, that occur before the patients show visible symptoms.Scientists around the world truly believe, that nanotechnology in fact is the future of medicine and that this emerging technology, although still in a “newborn” state, would provide answers for the treatment of many to this date incurable disease, as AD itself. Discussed approaches are still in an experimental phase, because the possible toxicology of many nanomaterials isn’t fully investigated.

The aim of present study was to investigate the effects of chemically synthesized of silver nanoparticles (Ag-NP) using citrate on selected blood biochemical parameters includes glucose, total cholesterol, triglyceride and total protein in rats model. In this study Ag-NP was synthesized with the usage of chemical reduction method. Laboratory rats were divided into four groups; control, placebo, and groups received 100 and 200 mg/kg BW of Ag-NP. Blood samples were taken, 15 days after administration, and separated serum was used for determination of biochemical measures. Greater dosage of Ag-NP (200 mg/ kg BW) causes mortality in experimental group, due to possible toxic effect of chemically synthesizedAg-NP. In serum biochemical measures infusion of Ag-NP had decreases serum glucose level (92 and 91 ml/dl in compared with control: 109 ml/dl), and total cholesterol and triglyceride had increases following Ag-NP administration (P< 0.01). In conduction, peripherally administration of chemically-synthesized Ag-NP in 100-200 mg/Kg of BW dosages, cause hypo-glycemic and hyper-lipidemic effects, due to increases peripheral glucose and decreases total cholesterol and triglyceride levels in rat model. The administration of greater dosage may cause mortality of experimental animals.

The ultimate goal of any economic, technological and social development is to improve human health and well-being. Thus, the society brings new requirements to new technologies, moving towards clean and green technology development. Green nanotechnology, as a branch of green technology, significantly contributes to environmental sustainability by producing nanomaterials and nanoproducts without harming human health and the environment, and by producing nanoproducts that provide solutions to environmental problems as well. Green nanotechnology is based on the existing principles of green chemistry and green engineering – it uses less materials and renewable inputs wherever possible, and thereby saving energy and fuel. The main benefits of green nanotechnology are: increased energy efficiency, reduced waste and greenhouse gas emissions, and minimized the consumption of non-renewable raw materials.

Bio-functionalization of nanoparticles with amino acids increases their biocompatibility and make them more efficient in delivery systems, especially in drug delivery and gene therapy. This can lead to development of new detection methods, in the field of clinical diagnostics, biosensors and DNA receptors. Alongside, understanding of the mechanism of amino acid adsorption on nanoparticle surface contributes to the evaluation of complex interaction between nanoparticles and proteins.Thus, development of methods for amino acid quantitation and characterization is very important. Still, the number of methods is very limited.We report a strategy for the quantification of cysteine adsorbed on gold, silver and silica nanoparticles by modified ninhydrin method. In order to obtain the most suitable ratio for amino acid adsorption, optimized parameters were: amino acid concentration, ratio of amino acids to nanoparticles, and nanoparticle concentration. Values of absorbance were measured by UV-Vis spectrophotometry and used for calculating the mass of adsorbed amino acid. The size of nanoparticles lacked an effect on amino acids whereas the ratio of amino acid to nanoparticles was revealed as a critical parameter. The method suggests 9:1 ratio as the most suitable for amino acid-nanoparticle interaction in case of both, gold and silica nanoparticles.

The biological surface adsorption index approach (BSAI) presents a novel approach for characterization of nanoparticles (NPs) in biological sys-tems. It is used for identification and quantitation of intermolecular forces that govern the adsorption properties of biomolecules on NPs surface. BSAI presents very important step in characterization of NPs-biomolecules interactions. Knowledge about the mechanism of interactions could help in prediction of NPs eventual toxicity in biological systems.Gold NPs are very often used in medicine, cosmetics and pharmacy thus evaluation of potential toxicity of gold NPs is extremely important prior its ap-plication.In this paper BSAI approach was applied on gold NPs with three different size (5 nm, 15 nm and 30 nm). The results showed that interactions of gold NPs and biomolecules vary in dependence of the size of NPs.The results contribute in toxicity assessment of gold nanoparticles in combi-nation with other analytical tools for toxicity assessment.

Dental implants, which are utilized for substituting missing teeth are appealed in clinical applications for decades. Moreover, they also are used for supporting craniofacial reconstructions and for orthodontic appliances. Besides having esthetically similar view to natural tooth, dental prostheses have no harmful effect to neighboring teeth and non-disturbing nature for the patient during mastication. On the other hand, the dental implant can result in bone resorption, biocompatibility problems and high costs. There are four main types of dental implant designs, which are developed and employed in clinical dentistry entitled as subperiosteal form, blade form, ramus frame, and endosseous form. From the beginning of this technic, a great evolution not only on implant design and surgical technologies of dental implants, but also on the classification of clinical success, failure and different surface treatments of dental implants is done. The failures are generally influenced on the mechanical properties of dental implants. Therefore, it is critical to estimate possible failures in a specific design of dental implant, which could protect the patients’ health and comfort. For this purpose, the experimental methods for the dental implants provide precise data for clinicians and engineers. Maximum allowable stress and strain, resonance frequency and resistance to fracture are key parameters to determine long term durability of dental implants. In this study, current status of frequently utilized mechanical tests to measure these properties, such as tensile, resonance and fracture tests are summarized. Test procedures with related standards, their strength and weaknesses are briefly discussed. This review is prepared to inform the tester about mechanical testing methods of dental implants in the light of recent advancements.

Physical interactions between patients and therapists during rehabilitation have served as motivation for the design of rehabilitation robots, yet there is a lack in fundamental understanding of the principles governing such human-human interactions. Review of the literature posed important open questions regarding sensorimotor interaction during human-human interactions that could facilitate the design of human-robot interactions and haptic interfaces for rehabilitation. The goal is to use the leading principles of the human-human interaction in order to define a way in which people could be in contact with robots in a more intuitive and biologically inspired way. The proposed hybrid impedance control solves the robot – environment contact problem and offers a possible solution for the rehabilitation robot interaction problem.

The gold standard for the analysis of human kinematics and kinetics is a camera-based motion capture system in combination with force measurement platforms. Alternatively, inertial measurement units can be utilized to obtain human kinematics, while ground reaction forces are computed from full body dynamics. This setup represents a system independent from the spatial confinement of a gait laboratory. The aim of this study is the comparison of the two methods by the investigation of lower limb kinematics and the resulting joint reaction forces within the ankle-, knee- and hip joints. For this purpose, human motion during gait was captured simultaneously by both measurement techniques. 13 trials from 8 different test subjects were evaluated in total. IMU data was processed with a quaternion based Kalman Filter. The data sets were implemented into a musculoskeletal simulation program in order to drive a virtual human body model. Each sensor was aligned to the gravitational and magnetic field vectors of the earth. The angles of flexions, extensions and rotations were analyzed to determine kinematic differences. Joint reaction forces defined kinetic dissimilarities. The overall kinematic differences of both models yielded root mean square errors of 7.62°, 6.02°, 4.95°, 2.79°, 2.38° and 3.56° for ankle flexion, subtalar eversion, knee flexion, hip external rotation, hip abduction and hip flexion, respectively. The proximo-distal differences in force peaks between the models yielded overall for the ankle, 57.33 %Bodyweight(BW) ± 46.86 %BW (16.66 %(Maximum peak to peak) ± 13.62 %) for the knee 37.09 %BW ± 29.33 %BW (17.65 % ± 15.44 %) and 32.03 %BW ± 24.33 %BW (15.6 % ± 12.54 %) for the hip. The overall outcome of this work investigated an approach independent of the common setup of the gait laboratory, thus enabling a cheaper and more flexible technology as an alternative. However, kinematic and thus kinetic differences remain rather large. Future work aims to improve the contact criterion for the calculation of the ground reaction forces and the implementation of a full-body calibration algorithm for the IMU system in order to counteract magnetic field disturbances.

Common Schanz screw systems can be used to stabilize pelvic ring fractures. In order to accommodate for different patient’s requirements, implants can be placed in cranio-caudal direction into the os ilium (T1), or into the supraacetabular bone canal, and thus, in dorso-ventral direction (T2). Whereas both techniques are currently used, no data of the biomechanical behavior is available up to this date. The aim of this study is to analyze, whether T2 shows biomechanical advantages with respect to tissue and implant stresses due to the enlarged bone-implant interface. Forces acting on the pelvis were analyzed using motion capture data of a gait cycle obtained by the utilization of a musculoskeletal simulation program. A three dimensional finite element (FE) model of the pelvis with grayscale-based material properties was generated. The muscle and joint reaction forces at toe-off were applied to the FE model and instable pelvis fractures were implemented. The osteosynthesis systems were positioned within the model in order to enable the comparison between the two different surgical techniques. Stresses and displacements were analyzed for bone tissue, fracture zone and implant.T2 lead to approx. 30% larger displacements in the fracture zone. Von-Mises stresses were larger for T2 in the implant (80 MPa vs. 227 MPa), whereas T1 leads to larger stresses in the bone tissue (200 MPa vs. 140 MPa).Both implantation techniques showed a good biomechanical behavior. Differences could be found with respect to tissue strains and deformations in the fracture zone. If bone quality or fracture healing are of concern, T2 or T1 should be used, respectively. However, both techniques seem to be applicable for cases with no special requirements. Further analyses aim to investigate the behavior under cyclic loading.

This paper presents research and development of hydraulically powered above-knee prosthesis (HAKP) and novel prosthetic foot, in order to enable transfemoral (TF) amputees perform stair ascent and other daily activities in as much as possible natural manner. Functions that need exertion of large forces and moments during locomotion such as walking up stairs and slopes cannot be naturally accomplished by commercially available microprocessor-controlled above-knee (AK) prostheses. Also, such prosthetic devices are expensive and unaffordable for major part of amputee population, so mostly used commercial prostheses are energetically passive devices. Deficiency of passive prosthetic devices is the lack of externally powered joints that could substitute a large number of missing muscles and provide a gait with the kinematics and dynamics similar to that of non-amputees.

Introduction: Robot assisted laparoscopic surgeries are becoming the standard procedure for radical prostatectomies (RALRP). General anesthesia, Trendelenburg positioning and capnoperitoneum during RALRP affect patient’ gas exchange, leading to possible complications in the postoperative phase, such as hypoxemia. The aim of this paper is to examine the changes in pulmonary gas exchange through the perioperative period for RALRP using a mathematical model approach.Methods: Measurements were performed with the Automatic Lung Parameter Estimator (ALPE) system, which include a mathematical model of pulmonary gas exchange capable of quantifying shunt and ventilation to perfusion (V̇A/Q̇) mismatch. In total, 20patients (ASA physical status I-III) with a mean age of 63.8 ± 6.6 years scheduled for elective RALRP at Aalborg University Hospital, where included in this study. Local procedures for anesthesia, ventilator settings and operation were followed throughout the study. Intraoperative measurements were performed before (T1) and during 30◦ Trendelenburg position and capnoperitoneum (T2-T3), as well as after exsufflation when the patients were returned to the supine position (T4).Results: Patients with ASA-score >1 had significantly higher shunt during and after surgery (T2-T4) compared to T1 (P<0.001).In the ASA=1 group there was no statistically difference between the levels. Moreover, the level of shunt at the end-point of surgery (T4) was significantly higher in the ASA>1 group compared to ASA=1 (P=0.02).At T1 there was no statistically differences in shunt between the groups. The level of V̇A/Q̇ mismatch did not increase significantly in the two groups, although when analyzed together in one group, there was a significant increase from T1 to T3 and T4(P=0.002).There was no differences between the level of V̇A/Q̇ mismatch between the groups at any timepoint.Discussion: In this a mathematical model approach was used to describe the perioperative development of shunt and V̇A/Q̇ mismatch for RALRP patients. The results showed an increase in both shunt andV̇A/Q̇-mismatch throughout the intraoperative period, with different patterns of development of shunt with the ASA score. This concurswith previous findings of oxygenation during anesthesia. This study provides an indication for the use of intraoperativeinterventions, such as increased PEEP and/or lung recruitment for patients with intraoperative V̇A/Q̇-mismatch and shunt, guided by a model-based quantification of the problems.

Introduction: Increased inflammatory markerscorrelate with progressive hypothyroidism. The link between subclinical hypothyroidism, subclinical inflammation and cardiovascular disease in postmenopausal women still remains unclear.Objective: To evaluate the association of subclinical hypothyroidism with inflammatory biomarkers and their impact on cardiovascular risk in postmenopausal women.Materials (subjects) and methods: Prospective clinical study included 140 postmenopausal women in the outpatient and diagnostic department of the Clinic for endocrinology in a tertiary university hospital. Sociodemographic and anthropometric data, thyroid hormonal status, inflammation markers (CRP, homocysteine, acidum uricum, IL-6, TNF-α) were obtained for all subjects. Theywere followed for 30 months and the incidence of cardiovascular disease was determined.Results: Subclinical hypothyroidism was associated with elevatedCRP, acidum uricum, homocysteine, and TNF-α. The incidence of cardiovascular disease was significantly higher in postmenopausal women with subclinical hypothyroidism compared to euthyroid women (p<0.001). Subclinical hypothyroidism was associated with higher cardiovascular risk regardless of age and duration of postmenopause (p=0.0007).Conclusion:Subclinical hypothyroidism is associated with elevated CRP, homocysteine, acidum uricum and TNF-α, and increases cardiovascular risk in postmenopausal women.

Treatment of Abdominal Aortic Aneurysm (AAA) is a challenge in vascular surgery. Latest methods used for treatment requires implantation of stent graft - particular synthetic blood vessel (graft) combined with armature (stent). We developed our software for surgical planning of implantation of stent graft for AAA. Material properties of the aortic wall were determined usingthe bubble inflation test method. Hardware-software system for acquisition of the tissue specimen displacement was developed. A specific image processing procedure for determining the relation between shear stress and drag force distribution was implemented for specific patient. Blood flow in the lumen wassimulated with Navier-Stokes and continuity equation. Fluid–structure interaction procedure for nonlinear deformation of the wall is used. Computational methods could be very helpful for patient-specific analyses and better understanding of the progression of AAA in a particular patient. Future clinical diagnostic systemcould use these complex computational surgical planning and AAA analysis.

In the last several decades the development of information-communication technology (ICT) and related fields has assisted medicine in many aspects. This paper tends to contribute to this ongoing trend by testing the accuracy of probabilistic neural network (PNN) trained to determine the results of cardiac stress test used for diagnosis of coronary/ischemic heart disease (CHD). The obtained results show that the network can determine the patients who really need immediate diagnosis treatments in the shortest time with the satisfactory accuracy. Therefore, the proposed simulations can be used for the physicians in the training process and additionally ease the work to cardiologists and improve the treatment of cardiac patients.

Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. It is proven that electrical stimulation could accelerate wound or fracture healing and also decreases pain. Because of numerous benefits on cell function, it is assumed that electrical stimulation can have positive effect on diabetes. Aim of this article is to summarize results of different studies which analyzed effect of electrical stimulation on most important parameters of diabetes mellitus in animal models. Unilateral electrical stimulation of dorsal motor nucleus of the vagus nerve resulted in rapid rise in plasma insulin levels >200%, and stimulation of the nucleus tractus solitarius, also produced 50% increase in insulinemia, in Wistar rats. Mild electrical stimulation (MES) combined with heath shock treatment (HS), significantly decreased fasting blood glucose and insulin levels, and improved insulin sensitivity in C57BL/6J, db/db mice as well as in KKAy mice. Peripheral electrical stimulation (PES) increased hepatic glucose output during the basal state in insulin-resistant Wistar-Han rats. PES improved tissue sensitivity to insulin, improved suppression of hepatic glucose production, and significantly elevated rate of glycogenesis compared with controls. Hepatic electrical stimulation was effective in reducing blood glucose by 27-31%, in Sprague-Dawley rats, streptozocin induced diabetic rats and Fa/Fa diabetic fatty rats. The present studies indicate that electrical stimulation treatment of very short duration is very potent to stimulate glucose uptake and improve insulin sensitivity. Electrical stimulation may directly affect major insulin target tissues or leading to secondary effects in other tissues. Low intensity current showed no observable adverse effects, but electrical conductance in cells should be measured. Electrical stimulation has very positive impact on diabetes in animal models, so it should be subject of further examinations for human use.

Cardiovascular diseases are the most common cause of death for humans in the last decade. Understanding of the fluid flow through the aortic arch, flow properties and the influence of the blood flow on aorta’s wall to make better predictions on the progress of disease. The geometric model of aortic arch is created from the series of CT scans, so that 3D model is generated. Finite-volume method is used for discretization of the equations describing blood flow. Velocity profiles, flow structure, creation of secondary and reverse flow, pressure drop on different control volumes of aortic arch are shown. Relation between the secondary flow and aortic arteriosclerosis development is confirmed. The phenomena of reverse flow in certain moment of cardiac cycle, given by the numerical simulations, coincide with theoretical and experimental results. Numerical simulations are used for better understanding and prediction of conditions triggering diseases such as aortic aneurysm and arteriosclerosis. CFD could have a significant role in detection, early prediction and treatment of the diseases.

Computational study for plaque formation and development for the patient specific coronary arteries was performed. Transport of macrophages and oxidized LDL distribution for the initial plaque grow model inside the intimal area was implemented. Mass transport of LDL through the wall and the simplified inflammatory process was firstly solved. The Navier-Stokes equations govern the blood motion in the lumen, the Darcy law is used for model blood filtration, Kedem-Katchalsky equations for the solute and flux exchanges between the lumen and the intima. The system of three additional reaction-diffusion equations that models the inflammatory process and lesion growth model in the intima was used. Some examples of computer simulation for plaque formation and progression for the specific patient for left and right coronary arteries are presented. Determination of plaque location and plaque volume with computer simulation for a specific patient shows a potential benefit for prediction of disease progression.

In this work, we address a problem of people identification. People identification is an important feature in various application like using in banks, airports, border crossings etc. For purpose of people identification today are used different methods such as face recognition, fingerprint, scanning of eye retina, voice recognition etc. The most of these methods require interaction with people while one method, people gait recognition, can be proceeding even without awareness of people who is in process of identification. Because of that, people gait recognition is interesting field in identification process and biometrical techniques. Our approach for this imply using Kinect sensor from Microsoft and Matlab high level technical computing language. For image classification we use bag of features or bag of words. Process consists of extracting regions, compute descriptors, find clusters, and compute distance matrix and using SVM (Support Vector Machine) for Classification. Dataset which is used in this process is also created with Kinect sensor.

The objective of this paper is to describe development of gas recognition tool based on Artificial Neural Network (ANN). This recognition tool has capability to recognize five different gases: ammonia, acetaldehyde, acetone, ethylene, and ethanol. Developed ANN is trained using data from the UC Irvine Machine Learning Repository database from October, 2013. The implemented system for gas recognition uses following input parameters: concentration of gas (ppmv), flammability, constant pressure (kJ/kgK), constant volume (Kj/kgK), specific heat capacities (cp/cv) and molecular weight (g/mol). Developed neural network consists of 30 neurons distributed in a single hidden layer.For purpose of training 174 samples were used. Testing dataset contained 64 samples, 38 of which were used as a testing set. With 36 samples correctly classified resulting in accuracy and specificity were 97.37%. These results were obtained after adjusting neural network using several different parameters which is explained in this paper.

Urinary tract infections (UTIs) are among the most common bacterial infections and account for a significant part of the workload in clinical microbiology laboratories. Hence, urine is the specimen most frequently submitted for culture. Physicians distinguish UTIs from other diseases that have similar clinical presentations with use of a small number of tests to distinguish bacteriuria. The microbiological examination of urine consists of examining a methylene smear of the urine specimen, a screening test of significant bacteriuria and culture. In the smear one or more bacterial cells per oil-immersion field usually implies that there are 105 or more bacteria per milliliter in the specimen, the number of RBC and WBC is also a very important indicator. In literature, the normal ranges of these variables are differently defined. The analysis of this data could be very simplified using data management systems. Fuzzy logic, in a narrow sense, is a logical system, which is an extension of multivalued logic. The fuzzy logic works on a theory which relates to classes of objects with blurred boundaries in which membership is a matter of degree. This enables fuzzy systems applicable to broad range of parameters and expected output values in many aspects of science. The aim of this study was to create a fuzzy model, in the MATLAB environment, to aid physicians in interpreting the results of the microscopic urine analysis, considering the number of bacteria, RBC and WBC as well as turbidity of the sample.

The conceptual representation allows visually differentiated understanding of certain ideas or structures. This simplified representation is used for easy understanding, and the understanding of certain idea/ structure whereby observer form a complete picture of the way in which he sees his mind, easily understandable to himself. Conceptual design of the anatomy of the heart, vascularization, and a conceptual design of theoretical occurrence of obstruction and involvement of a certain wall in relation to the occurrence of ST segment elevation that occurs in ECG display of myocardial infarction has importance in: display of places of obstruction of the patient, easier patient’s understanding of the problem, representation is important in the education of students, when performing practical part of the basic, pre-clinical medical subjects, theoretical possibility of using the conceptual design in the software connection with modern ECG devices, which would next to the finding, promptly show the place of obstruction, and conceptual design allows to add additional pathology of the heart, where it can take into account various disorders in the anatomical structure of the heart, or heart muscle.

Gait event detection has been widely implemented in real-time gait monitoring devices, orthoses and FES system. Certainly, the latency and the accuracy of the gait-even detection under diversities of gait are crucial. However, due to the high detection accuracy usually comes with high time-delay, it is somewhat hard to find a trade-off between high accuracy and low latency. Therefore, this paper presents a real-time algorithm based on wireless inertial sensor placed on the shank for gait-even detection. It combines the use of the cycle-extremum and the updating threshold method to detected the heel-strike (HS), as the minimum of the flexion/extension angle, the toe-off (TO), as minimum of the angular velocity and the mid-swing (MS), as maximum of the angular velocity. The angle and angular velocity were collected from 2 subjects who imitated the patient that suffered from drop-foot for different degrees to validate the algorithm against the wireless inertial measurement system. The results showed that the proposed method achieved comparable levels of accuracy and significant lower detection delays compared with other published methods.

The goal of this paper is to present the development of a phase modulated signal generator and receiver pair that are designed with intrabody communication (IBC) purposes in mind. The system is to be implemented using Programmable System-on-Chip (PSoC) microcontrollers produced by Cypress. The design and the firmware are to be implemented in Cypress PSoC Creator for the CY8C5888LTI-LP097.

Transdermal drug delivery offers a number of advantages including sustained release, improved patient compliance, avoidance of gastric irritation, as well as elimination of pre-systemic first-pass effect. However, only few medications can be delivered through the transdermal route in therapeutic amounts. NSAIDs are consisted of a group of drugs that are widely used, but their use by oral or transdermal system is limited due to a number of side effects. Therefore, NSAIDs are ideal candidates for delivery via microneedles, a relatively new method of drug delivery. A new concept was introduced known as microneedles and these could be used to effectively deliver drugs using micron-sized needles in a minimally invasive and painless manner. Microneedles can be used to enhance transdermal drug delivery and they can be fabricated in different forms.

High energy methods include high pressure homogenization, microfluidization, sonication, method in jet disperser, high-amplitude ultrasonic method. The droplet size of the dispersed phase in nanoemulsions produced in a high pressure homogenizer declines with increasing of the number of homogenization cycles its, lowering of surface tension, the increasing the rate of surfactant adsorption and decreasing the ratio of viscosity of the dispersed and continuous phase to some extent. The droplet size of the dispersed phase of nanoemulsions produced in microfluidizer decreases with the increase of homogenization pressure, the increase of the number of passages of nanoemulsion through microchannels, the increase of the concentration of surfactant and decrease of the ratio of the dispersed and continuous phases’s viscosities. The droplet size of the dispersed phase in nanoemulsions produced by sonication decreases with increasing duration of ultrasonic homogenization, power levels and concentration of surfactant. Only small amounts of nanoemulsion formulations can be prepared by this method.The low-energy methods are: spontaneous emulsification, phase inversion methods, and solvent displacement method. Phase transition in the phase inversion methods, occures when the temperature is changed while the composition is constant or the temperature is kept constant with changing composition. The mixture of oil, water and nonionic surfactant at room temperature shows a positive curvature. In the phase inversion temperature method rapid temperature changes prevent coalescence and produce stable nanoemulsions. A large ratio of solvent and oil is required for the production of small diameter droplets of the disperse phase by solvent displacement method.High-energy methods, such as homogenization under pressure, can be prepared with the nanoemulsion droplet sizes up to 1 nm, and nanoemulsion with uniform droplet size of the disperse phase. Low energy methods are more acceptable for manufacturers because they do not require expensive equipment.

The aim of this paper was to analyse the characteristic properties of different commercially available NiTi archwires (diameter 0.014”). Characteristic properties were determined by using DSC analysis for identification of phase temperatures and a tensile test for obtaining the mechanical properties, while semi-quantitative EDS analysis was used for their chemical composition. Analysis of phase temperatures showed that nickel- titanium orthodontic archwires, in the austenitic phase, were exhibiting superelastic effect in the oral environment (T= 37°C). The uniaxial stress-strain curves showed different values for the beginning and the end of loading due to the stress and transformation range. The investigation of the chemical composition showed an equiatomic NiTi alloy.The aim of the first phase of biocompatibility assessment of Ni-Ti archwires was to investigate the potential cytotoxicity on a model of rat thymocytes, where a direct contact exists between the archwire and the cells. The test was chosen because of the high sensitivity of thymocytes to pro-apoptotic stimuli and because the test includes the culture of non-adherent, non-proliferating cells, such as thymocytes, which is much more convenient for the evaluation of a material’s cytotoxicity in direct contact, compared to the adherent cells such as fibroblasts. The experiment was designed to cultivate the Ni- Ti archwire samples with rat thymocytes, using different surface-over-volume ratios of the archwires in complete medium. The cytotoxic effect was evaluated by measuring the apoptosis. The aim of the second phase of the study was to investigate further the cytotoxic effects of Ni-Ti archwires in the short-term (24h) and long-term (48h) cultures of rat’s thymocytes, which are highly sensitive to pro-apoptotic stimuli, where a direct contact exists between archwires and the cells.

The aim of the present study was to investigate the effect of co-activation of antagonist muscles on long-latency intracortical inhibition (LICI) in comparison to isometric index finger abduction. EMG signals were recorded from the first dorsal interosseous muscle (FDI) in response to single-pulse and paired-pulse transcranial magnetic stimulation (TMS).In 10 healthy right-handed volunteers, TMS was used to estimate LICI at 3 different interstimulus intervals (ISIs) - 50, 100 and 150 ms. The intensity of the conditioning and test stimuli was 130 % of the motor threshold in relax. The stimulation procedure was repeated at rest and during tonic isometric index finger abduction and co-activation of antagonist muscles.At rest, LICI was significant at ISIs of 100 and 150 ms and not evident at ISI of 50 ms. During isometric index finger abduction and co-activation of antagonist muscles, LICI was evident at all used ISIs and was even better pronounced at 50 ms. At ISIs of 50 and 100 ms during abduction, LICI was significantly stronger in comparison to co-activation.During abduction and paired-pulse TMS, the mean values of cSP at all used ISIs were significantly shorter compared to single-pulse TMS. The shortening of cSP recorded in response to paired-pulse TMS was gradual, with increasing of ISI from 50 to 150 ms. In contrast, during co-activation, the duration of cSP was almost independent of the value of ISI and similar to the duration of cSP in response to single-pulse TMS.

Beside the possibility to actively control the amount of damping in artificial joints, modern prosthetic devices should have the ability to generate power. This would enable persons with amputation to achieve biologically realistic kinematics and dynamics of locomotion.Recent development in prosthetics is primarily influenced by new knowledge and research performed in the field of human body biomechanics. Tracking of human body motion is based on the use of appropriate optical or magnetic markers, which are placed on specific landmark points, and real-time estimating of their spatial coordinates. With the improvements introduced in computer monitoring of human motion, it is important to lay emphasis on the significance of combining motion capture data with commercial CAD packages, in order to conduct detailed motion analysis and evaluate the mechanical performance of prosthetic design using CAD virtual models.This paper presents a method of determining the functional dependence of relevant kinematic parameters on prosthetic devices, in order to define a set of data for the development of appropriate control systems for achieving the desired movement pattern. The functional dependence of change in length and velocity of linear actuators built into the knee and ankle joint of the powered transfemoral prosthesis has been analysed. These data can be used to enhance the control systemduringthe stance period of stair ascent, in order to achieve biologically equivalent locomotion.

Thyroid pathology is the second largest disease after diabetes in endocrinology. In patients with thyroid dysfunction an increase in bleeding time, activated partial thromboplastin time (aPTT) activated recalcification time (ATS), the clotting time are observed.The most important role in the physiology and pathology of coagulation platelets play. Hypothyroidism can alter platelet function, changing Adenozin diphosphate-induced aggregation. Violations of activation platelets: slowing or stopping the adhesion and aggregation, increased disaggregation can lead to severe hemorrhage. According to the study in patients with thyroid dysfunction are observed: lengthening of APTT, increased levels of fibrinogen, reflecting a tendency to anticoagulation, reducing the total number of platelets, decreased platelet aggregation activity, growth of aggregation speed, reduction of the maximum aggregate size and elongation of maximum speed value. Patients with elongation of APTT and fibrinogen increase indicate a rapid continuous intravascular coagulation, accompanied by moderate hypocoagulation of consumption – reducing the number of platelets allows to suggest the consumption. More significant are hemostatic changes in patients with multinodular non-toxic goiter with respect to shifts in patients with hypothyroidism. More important changes are in clotting and platelet activation in patients with the simultaneous occurrence of hypothyroidism and nontoxic multinodular goiter. The presence of signs of acceleration of intravascular coagulation, as measured by the fibrinogen content, allows to suggest that hypocoagulation is not associated with the property of thyroid hormones to reduce the activity or production of plasma-coagulation factors, or increase anticoagulant blood potential. More likely, hypocoagulation is secondary - due to the activation of the WTF, leading to accelerated consumption of clotting factors. Decreased platelet content shows the consumption.Thus, in patients with impaired thyroid function coagulation system is under stress, expressed by the development of signs of DIC with a chronic course, these changes are manifested more deeply in patients with uninodule nontoxic goiter.

Introduction: Despite measures done to avoid neonatal respiratory distress syndrome, many prematurely born infants still suffer from this disease, they are artificially ventilated, or experience long term oxygen dependency and consequently have chronic lung disease/bronchopulmonary dysplasia. One of the proposed measures for shortening of mechanical ventilation is strategy of permissive hypercapnia. There are promising studies, but clear recommendations for this treatment option are still lacking.Aim: The aim of this study is to determine number of patients ventilated by permissive hypercapnia, and to analyze factors that lead neonatologists towards decision to treat preterm infants by this ventilation option.Methods: The present study was conducted in a tertiary research and educational hospital from April 2013 to July 2015. At admission we registered data regarding birth weight, gestational age, Apgar score, prenatally given steroids, mode of delivery, CRIB score. All infants had chest X-ray at admission. When establishing diagnosis of respiratory distress syndrome and conducting its treatment, we followed European Consensus Guidelines on the Management of Neonatal Respiratory Distress Syndrome in Preterm Infants – 2013 Update. After treatment, according to their mean PaCO2 patients were divided into hypercapnia and normocapnia group, and then analyzed.Results: There were 69/158 (43.7%) patients in hypercapnia (HP) group and 89/158 (56.3%) in normocapnia (NC) group. Out of total number of patients 48.7% were female. Mean PCO2 in PH was 7.46 kPa (range 6.3-10.6 kPa). In NC group mean PCO2 was 5.9kPa (range 4.6-7.3kPa). Two groups didn’t differ regarding gestational age, prenatally given steroids, Apgar in 1. and 5.minute, mode of delivery, CRIB score, nor according to level of respiratory distress syndrome, and surfactant use. Group of neonates ventilated by strategy of permissive hypercapnia had significantly higher mean birth weight P=0.029.Conclusion: This study shows that in absence of clear recommendations and defined criteria for implementing strategy of permissive hypercapnia in prematurely born infants, in praxis we find almost half of the babies who have been treated by this mode of respiratory treatment. For this ventilation option neonatologists prefer children with higher birth weight.

Diabetes mellitus is a metabolic disorder representing one of the main problems for the global public health. The impairment of metabolic control can influence periarticular tissue and other major risk factors of limited joint mobility (LJM) also in young type 1 diabetic patients. LJM is a widespread phenomenon in diabetic patients and it is often characterized by ankle stiffness. In particular, a deficit of ankle joint mobility may occur with the onset of the disease; later, this deficit tends to deteriorate in presence of a poor glycemic control. We hypothesized a mathematical model of diabetes mellitus long-term effects, assuming that a reduced metabolic control affects joint mobility according with a Gaussian function: it requires some time for developing a reduction of joint mobility, that persists for a stable period, before fading out with time (in case metabolic control has been recovered). A non-linear optimization estimated the model parameters for obtaining the best fit over a set of patients. Results are in good accordance with empirical estimates: lack of control needs to persist for at least a few months before generating a sensible effect, that persists for up to one year.

The human cardiovascular-respiratory system is a complex system which exhibits the properties of a control system of the regulator type. The gas exchange combines many processes that occur in the brain, lungs, vasculature, and body tissues. This paper deals with a simple model that provides a linearized description of pulmonary ventilation mechanics. Some equations describing the introduction to chemical regulation of lung ventilation are derived.

Experimental data of the influence of media’s pH value on the solubility and partition coefficient of the acetylsalicylic acid (ASA) is presented in order to define the place in the human digestive system where ASA is absorbed after oral administration.The solubility of ASA in three media with different pH value (pH 1.2; purified water and pH 7.4) was determined using UV spectrophotometric measurement (based on Beer-Lambert’s law that says that absorbance represents the linear function of concentration). Data for partition coefficient calculating was obtained by using classical shake-flask method, whereby as polar phase previously mentioned media were used and as organic phase chloroform was used.The study showed that both solubility and partition coefficient are pH-dependent, whereby solubility increases with increasing pH value above the pKa value, while partition coefficient decreases in the same conditions.ASA is theoretically expected to be the best absorbed in a medium where it is mostly presented in the unionized form. In this case, it is a hydrochloric acid buffer (pH value 1.2) which is similar to one found in the stomach. However, data from previous experimental studies have shown that ASA is the best absorbed in the proximal small intestine, due to larger surface area and more permeable membranes.

Osteoporosis is a skeletal disorder which weakens the bones and increases the risk of the bone cracking. There are many factors included in the pathogenesis of osteoporosis and a lot of them still remain unknown. The RANK/RANKL system is involved in osteoclast maturation. By binding to its receptor (RANK), RANKL stimulates osteoclast precursors to develop into fully mature osteoclasts. RANK transmits biochemical signals after the recruitment of the intracellular adaptor TNF receptor associated factor (TRAF) proteins. TRAF6 binds to RANK and plays an essential role in RANKL-mediated NF-κβ activation in transfected cell systems.The Eukaryotic Linear Motif (ELM) and MiniMotif Miner (MnM) servers are web-based tools that can be very useful to identify small linear sequences, called motifs.In this paper, we have researched the possibility to predict some protein functions with ELM and MnM servers, using an example of RANK protein interactions with other proteins involved in osteoclast maturation. We couldn’t find prediction of the experimentally proven RANK/RANKL interaction, but on the other hand, the prediction for the RANK/TRAF interactions where mostly true. The use of these tools can be a good starting point for the research of unknown protein functions, but every claim has to be experimentally proven afterwards.

Phosphatidylinositol-3-kinase (PI3K) / mammalian target of rapamycin (mTOR) kinases belong to the phosphatidylinositol-3-kinase-related kinase (PIKK) family of kinases. Dysregulation of PI3K/mTOR signaling pathway is often detected in various types of malignancies and is correlated with a poor prognosis. PI3K and mTOR share considerable homology in the structure of their active sites and rational advantages of dual inhibition of PI3K/mTOR are known. In order to identify the most important structural determinants that influence antiproliferative activity, 3D-QSAR (quantitative structure activity relationship) studies were performed on two groups of structurally diverse PI3K/mTOR inhibitors. Created QSAR models passed internal and external validation allowing the reliable activity prediction of new PI3K/mTOR inhibitors that were designed based on the obtained 3D-pharmacophores. Initial pool of designed compounds was subjected to structure based virtual screening in order to select the best candidates. Results of this study may be very helpful in further discovery of selective PI3K/mTOR dual inhibitors as novel antineoplastics.

Biotechnology industry worldwide is an enormous industry, and in 2005 only in the US 1400 biotechnology companies with trades worth $419 billion was registered. Green biotechnology involves, among others, processes such as development of pest resistant plants, new plant derived drugs and new nutritive plants. Research in this area offers possibilities for the development of new food products and mechanisms for the control of pathogenic agents in foods. In Bosnia and Herzegovina green biotechnology is slowly developing branch of biotechnology. If we consider last two years, green biotechnology in Bosnia and Herzegovina produced less than 10 research papers, in the same time period neighbouring countries have developed research laboratories for green biotechnology and are successfully applying for HORIZON 2020 grants (example of Sinisa Stanković Institute – FP7 - Plant Terpenoids for Human Health: a chemical and genomic approach to identify and produce bioactive compounds). Why is this the case? First of all the average laboratory for plant in vitro culture oriented for evaluation of gene expression and metabolic engineering costs around 1 million euros. The field is constantly evolving and the costs of making the laboratory productive rises even more. Governmental supported projects in B&H are usually around 10 000 euros and it is impossible to establish such laboratory without international projects. HORIZON 2020 usually seen as a golden goose by the researchers, offers large projects but for a scientist, dealing with green biotechnology, from Bosnia and Herzegovina (speaking from my own experience, after 8 years working in green biotechnology field) to apply for such founds is a borderline science fiction. We are enclosed in vicious circle of different roadblocks in the process of making green biotechnology interesting for the researchers and students in Bosnia and Herzegovina. First of all funding of the green biotechnology projects is usually considered to be less important than biomedical engineering. We are forgetting that in pursuit for new medicines in this era of the emergence of antibiotic resistance we must return our focus to green biotechnology and plant metabolic engineering. By stimulating students to pursue career in green biotechnology we are investing in our future, in new medicines, in new food products and crop resistant to pests. For this reason, by developing better plants we are stopping the consequences before they emerge, like the effects of pesticides.

The rapid advancements in Information and Communications Technologies (ICTs) and the increasing number of smart things (portable devices and sensors) enable the transfer of health resources and healthcare by electronic means. This is known as e-health, and today is closely related to the Internet, which provides a new medium for dissemination of healthcare-related information and for interaction and collaboration among institutions, health professionals, health providers and the public. Increased efficiency in healthcare, improved quality of care, availability, responsibility and satisfaction of patients and consumers are the main benefits e-health offers. Unfortunately, there are many challenges associated with e-health adoption, especially in developing countries like Bosnia and Herzegovina. To understand and address the challenges of implementing and adopting e-health in Bosnia and Herzegovina, this paper presents a review which identifies the main political, economic and technological challenges for widespread e-health adoption.

The concentration of metabolites of neurohormones in cerebrospinal fluid (CSF) is an index of turnover of substances in brain. 5-Hydroxyindoleacetic acid (5-HIAA) – serotonine metabolite and homovanillic acid (HVA) - dopamine metabolite, were studied in CSF of patients with coma cerebri, hydrocephalus and tumor cerebri. CSF concentrations of 5-HIAA and HVA were determined in 140 patients of different age and sex. The samples were analyzed for 5-HIAA and HVA by high pressure liquid chromatography with electrochemical detector (HPLC-ED). Average concentration of 5-HIAA was 9.54 +/- 2.09 ng/mL, and for HVA it was 27.17 +/- 4.39 ng/mL. Average concentration of 5-HIAA in CSF of male subjects was 13.39 +/- 3.30 ng/mL, and for female subjects 4.23 +/- 1.34 ng/mL. Average concentration of HVA in CSF of male subjects was 31.52 +/- 4.86 ng/mL, and for female subjects 21.19 +/- 3.70 ng/mL (p<0.05). Results increased 5-HIAA and HVA concentration in CSF in comparison with other pathochemical conditions, such as acute lymphocyte leukemia, encephalitis, meningitis serosus, multiple sclerosis, quadriplegia and sepsis. Long-term follow-up is required to assess if they could be of prognostic significance as regards to long term attainment of brain functions in coma cerebri, hydrocephalus and tumor cerebri patients.

During the early stages of drug discovery, it is very important to determine lipophilicity and to investigate and predict processes of drug distribution and resorption in human body, i.e. their bioavailability. Novel fourteen compounds representing ester derivatives of (S,S)-1,2-ethanediamme-N,$$ N^{\prime } $$-di-2- (3-cyclohexyl)propanoic and (S,S)-1,3-propanediamine-N,$$ N^{\prime } $$-di-2-(3- cyclohexyl)propanoic acids, expressing antiproliferative activity in vitro were examined. The objective of this study was to estimation a lipophilicity data of observed fourteen compounds by ultra-high performance liquid chromatographic tandem mass spectrometry (UHPLC-MS) method. It was used gradient and isocratic method to obtain chromatographic parameters of lipophilicity/hydrophobicity, which are needed for calculated logP values. Results of lipophilicity data for observed 14 compounds, which were obtained by UHPLC-MS method and presented in this paper, are showed that the derivatives of 1,2-ethandiamine-N,N’-di-2-(3-cyclohexyl) propanoic acid have higer values of logP, than derivatives of 1,3-propanediamine-N,N’-di-2-(3-cyclohexyl) propanoic acid. Also, value of lipophilicity data for each of investigated compounds depends on the length of the alkyl chain on the esters bounds. Branching of the alkyl chain on the esters bounds has insignificant influence on the values of lip ophilicity/hydrophobicity.

Peroxidase is classified as oxido reductive enzyme which catalyzes the oxidation of the substrate by a hydrogen peroxide solution, the composition of a protein which is the prosthetic group of HEM. Inthispaper,the effect of active substance from the different groups of drugs on peroxidase activity was studied. Electro chemical tests were performedinclassical three– electrode system with techniques of cyclic voltametry and chronoamperometry. Ampero metric biosensor for the determination of H2O2 is presented,based on GC electrode on which per oxidase is immobilized in Nafion film.Cyclic voltametry technique was used to research the influence of different substrate concentration on the enzyme activity in a potential range between – 1,0V and 0,7V and scanrate of 50mV/s.Chrono amperometric technique was used for the determination of kinetic parameters Km and Vmax ataconstant potential of 0,9V.

Stability studies of drugs by stress study is a very important process which is done by treating the study drug with different stress agents, with the aim to define the critical factors affecting the stability of the drug, to accurately define the storage conditions of the drug, as well as to identify the resulting degradation products. In this paper, stress studies of bisoprolol fumarate were performed, in order to examine what are the stress agents that affect its stability.For the analysis previously optimized and validated HILIC method was usedIt was demonstrated that oxidative stress agent has the largest effect on the degradation of bisoprolol fumarate, and then the acid and base stress agent successively. Water, as a neutral medium, and light had no significant effect on the stability of bisoprolol fumarate. During degradation under acid conditions impurity A was formed and it was confirmed with UPLC/MS/MS method. In order to more clearly define the processes of degradation, kinetic studies of degradation of bisoprolol fumarate have been carried out, in order to determine the order of the reaction rate of degradation and degradation half-time, which provided clearer definition of the mechanism of degradation.

Sensory features of cosmetic products are one of their most important characteristics for consumer acceptance. Consumers preferably choose one product among many based on their perceptions: first of its packaging, and then of its smell, appearance and texture (touch and feel). When optimizing a product, in order to adapt it to the needs and desires of consumers, cosmetic companies use sensory evaluation methods. They require trained panels making them time-consuming and expensive.On the other hand, rheological measurements and textural analysis are instrumental methods that offer fairly simpler, less expensive and much less time-consuming means of analysis, at the same time giving more objective and repeatable results.Finding correlations between sensorial assessments and instrumental analyses, and being able to use instrumental instead of sensorial analyses would have great benefits in the development of cosmetic products. However, this is not an easily accomplished task.In the available literature there are examples of these kind of studies on cosmetic emulsion systems (creams and lotions), but also on gels, foundations and raw materials. The prediction models are rarely developed and validated for having instrumental in lieu of sensory assessments.These studies are very versatile in terms of chosen sensory attributes and, even more so, in terms of studied instrumental methods and chosen parameters. Therefore, it is very difficult to compare them and find matching correlations. As sensorial analyses are being developed and new instrumental analytical techniques introduced with supporting sophisticated softwares, the number of studied parameters increases and new correlations are being made.It is still a worthy goal, however, to be able to instrumentally predict at least basic sensations associated with the use of cosmetic products to be used for screening in developmental phases of their making.

The aim of this study was to evaluate the total hydrophilic antioxidant scores (THAS) against peroxyl (ROO•) and hydroxyl (OH•) free radicals in different types (d.t.) of bee honey from Bosnia and Herzegovina (B&H). It has been analyzed 46 honey samples of d.t. such as: meadow honey (MeH), acacia honey (AH), forest honey (FH), mountain honey (MoH), heather honey (HH), and chestnut honey (CH). All analyses were performed by oxygen radical absorbance capacity (ORAC) assay, using trolox as a standard. Antioxidant capacity (AC) against ROO• and OH• (AC_ROO• and AC_OH•) expressed as trolox equivalents per honey weight (mM TE/g): as the THAS [(AC_(LA+HA)ROO•+AC_(LA+HA)OH•), AC derived from low-molecular and high-molecular weight antioxidants (LA and HA, respectively) together in the bulk], then as the HAS against ROO• and OH• derived from LA only (HAS_(LA)), and as the HAS against ROO• and OH• derived from HA only (HAS_(HA)). ORAC analysis showed that THAS d.t. of honeys decreased as follows FH>HH>AH>MoH>MeH>CH, then HAS_(LA) d.t. of honeys decreased as follows MoH>FH>AH>HH>MeH>CH. Also, HAS_(HA) for AH was higher than HAS_(HA) for MeH.Based on obtained results, it can be concluded that bee honey from B&H has a significant AC against ROO• and OH•.

The 1691G>A FV polymorphism is considered to be one of the leading genetic risk factors of pregnancy loss. Recently, also other heritable factors of thrombophilia that may predispose to microthrombosis mainly in trophoblast or placenta leading to obstetrical complications attract an attention. In recent studies it was found that both, 1691G>A FV and 4070 A>G FV polymorphisms may increase risk of pregnancy loss, and double heterozygosity for 1691G>A FV and 4070A>G FV conferred a 3- to 4-fold increase in the relative risk of venous thromboembolism compared with 1691G>A FV alone. Aim: We decided to determine the prevalence of 1691G>A FV (rs6025) and 4070A>G FV (rs1800595) polymorphisms in women with pregnancy loss, as well as in women without previous miscarriages. Another aim was to determine the possible association between 1691G>A and 4070A>G FV polymorphisms and a risk of pregnancy loss. Material and methods: Based on medical history, 154 women, mean age 33.0 (±5.4) years, that had one or more spontaneous pregnancy loss and 154 women without previous pregnancy loss with at least one live-born child, mean age 31.4 (±6.7) years were enrolled. Following DNA isolation from buccal swabs, real-time PCR for 1691G>A FV and PCR-RFLP for 4070A>G FV were done. Results: In woman with pregnancy loss we identified: 142 GG homozygotes, 12 GA heterozygotes and none AA homozygotes of 1691G>A FV, and 125 AA homozygotes, 27 AG heterozygotes and 2 GG homozygotes of 4070A>G FV, while in controls 142 GG homozygotes, 12 GA heterozygotes and none AA homozygotes of 1691G>A FV and 123 AA homozygotes, 28 AG heterozygotes and 3 GG homozygotes of 4070A>G FV. The prevalence of 1691G>A and 4070A>G FV polymorphisms are consistent with data for other European populations. We observed coinheritance mutated alleles 1691A and 4070G in 3 women with pregnancy loss, but it was not statistically significant compared to the control group,(p>0.05. We did not observe any differences in the prevalence of the genotypes and frequency of alleles in women with pregnancy loss compared to women without pregnancy loss, (p>0.05). Conclusion: Our results, did not confirm association between the prevalence of 1691G>A and 4070A>G FV and pregnancy loss in Bosnian women.

Successful pregnancies, among others, require stabilization of the placental basal plate, preventing accumulation of fibrin in placental vessels and intervillous spaces. Fibrinolysis is regulated by PAI-1, which synthesis is induced by angiotensin II, which is being generated by ACE I. In recent studies, it was found that -675 ID, 4G/5G PAI-1 gene polymorphism, as referred to “a new thrombophilic factor” may increase risk of pregnancy loss. Data on prevalence of genetic risk factors of thrombophilia in Bosnia and Herzegovina (B&H) are rare. Aim: Therefore, we aimed to determine prevalence of I/D ACE (rs l799752) and -675 ID, 4G/5G PAI-1 (rs 1799889) polymorphisms in Bosnian women with pregnancy loss and evaluate the results of the risk of miscarriages. Material and Methods: We prospectively recruited 308 women in total, particulary 154 women with pregnancy loss (PL), mean age 33.0 (±5.4) years and 154 controls without pregnancy loss, at least one liveborn child, mean age 31.4 (±6.7) years. All women were enrolled from Institution of Health Protection of Women and Motherhood (Sarajevo, B&H). Following DNA isolation from buccal swabs, PCR for ACE and real-time PCR for PAI-1 was performed. Results: In women with PL and controls, the frequencies of D and 4G alleles were: 52.3% and 55.5% and 60.1% and 59.7%, respectively. There was no difference of frequency of mutated alleles in group of PL compared to the controls (p>0.05). Conclusion: Our results, did not confirm association of I/D ACE and -675 ID, 4G/5G PAI-1 polymorphisms with pregnancy loss in examined population.

This paper presents the results of a study developing gene clustering of cancer patient’s data using gene expression data and Self-Organizing Maps (SOM). The SOM used in this paper was especially designed for patients with myelodysplastic syndromes and leukemia to reveal and present expression pattern for following disease progression since the disease itself is very aggressive. Developed SOM is self-trained using BloodSpot: a database of gene expression profiles for healthy and malignant hematopoiesis. Implemented system used expression data for IL3RA gene of cancer patients and healthy individuals containing 754 samples each. Developed SOM was made using 10x10 grid, thus 100 neurons, resulting in 100 outputs grouped in two differentiable clusters. The SOM was trained and validated using expression of NSMAF gene for both groups of individuals. Results obtained showed two successful clusters; one representing acute myeloid leukemia (AML) patients and the other representing healthy individuals. Using SOM maps the different expression patterns can be easily followed as well as used for finding a research factor for the specific disease.

Until 2009 Bosnia and Herzegovina was one of the few countries which didn’t have the law on genetically modified organisms (GMOs). The aim of this paper is to identify the public opinion on genetically modified organisms and biotechnology in Bosnia and Herzegovina where the survey is enforced. The survey included a handful of questions related to genetically modified (GM) crops, foods, one on the safety of foods and related products, and one of other uses of biotechnology (e.g. in human medicine). The age range of respondents was from 17 to 67 years and total of 734 respondents were interviewed. The answers are represented in the percentage. In conclusion, although respondents were mainly introduced with the term “GMO”, most of them were not satisfied with their knowledge and available information considering biotechnology and its use. We established that the participants displayed a pessimistic attitude which reflected a belief that the widespread use of GMOs is presenting a risk to human health and a risk to environment in a term of endangering native species. Participants only showed a little bit more positive opinion about the use of biotechnology in medicine and pharmacy.

Animal testing has shown unsatisfaction when it comes to examination of hepato- neuro- and cardiotoxicity, as well as in the development of new therapies, while use of in vitro model systems is limited by unavailability of human tissues. For this reason, use of human embryonic stem cells (hESC) as unlimited source for producing differentiated somatic progeny, represents a great medical advance.Induced pluripotent stem cells (iPSC) represent a new type of stem cells that occur by reprogramming of genomes of adult stem cells, such as dermal fibroblasts into a pluripotent state. These cells have many similarities with embryonic stem cells, and their reprogramming requests transcription factors OCT4, SOX2, and KLF4. IPSC are characterized by the ability of recovery and differentiation into different cell types such as pancreatic β-cells, hepatocytes, cardiomyocytes, hematopoietic cells, which opens the door to the new methods of treatment of many diseases especially in the field of personalized regenerative medicine. This paperwork contains future trends and possibilities of using iPSC’s in regenerative personalized medicine, and with great certainty we can say that the discovery of the same has brought a revolutionary changes to medicine, and that these cells will soon be used not only for modeling of various diseases, but also for treating diseases and finding and testing new drugs that will help to improve the quality of life in many patients.

In this paper classification algorithm of ECG signals based on segmentation of basic waveform using artificial neural networks was implemented. Inputs of classification process are different types of features: time-domain features, morphological features, statistical features. Comparison of results using these types of features as well as their combination was performed. The algorithms are implemented in MATLAB environment and performance of algorithms is evaluated on the MIT-BIH Arrhythmia Database. Feature extraction process was done using Wavelet transform (detection of P, Q, R, S, T waves for time-domain features and its coefficients for morphological features) and statistical functions. The best results were gained using morphological features in combination with their statistical features.

The Electromyogram (EMG) signals are used in exoskeleton robot control for the recognition of the electrical activity related to the muscle contractions. In this study, surface EMG signals are classified to recognize the different types of myoelectric signals. The performance of a classifier is affected by the variation of EMG signals due to the different categories of contraction. To avoid such variations, the Wavelet Packet Decomposition (WPD) is used for features extraction from surface EMG signals. Then, a set of features selection methods is employed to reduce the high-dimensional features. After a feature selection, different ensemble tree classifiers like Random Forest, Rotation Forest and MultiBoost are used for classification. Results are compared by using total classification accuracy, F-measure and Area Under ROC Curve (AUC). An effective combination of WPD and Random Forest achieves the best performance, using k-fold cross validation, with a total classification accuracy of 92.1%. The proposed methods in this study have potential applications in exoskeleton robot control and rehabilitation.

Heart Rate (HR) and Heart Rate Variability (HRV) are recognized and used in identifying and diagnosing different psychological conditions. HRV is also frequently used for diagnosing and monitoring autonomous nervous system. In this paper we propose a tool for analyzing HR and HRV in time and frequency domain, and using geometric analyses as Poincare plots for visualization. Implemented tool is designed to accommodate requirements of contemporary research in this area and extended for comparative analysis of sets of measurements. Case study analyzing correlation between HR measurements and stress levels for students before and after an exam is conducted. Measurements are used to illustrate the benefits of using the tool in creating and managing sets of measurements and their comparative analysis.

In this paper we presented a new approach for parameter estimation of Fricke-Morse model (2R-1C circuit) of biological cell. Proposed method is based on Differential Impedance Analysis and it was applied in parameter estimation of five electrical bioimpedances: Total Body Composition, Trunk-Trunk, Arm-Arm, Leg-Leg and Respiration Rate. The proposed method has been evaluated regarding the influence of the number of measurement frequencies on the overall numerical accuracy and processing time. Obtained results are compared with Complex Non Linear Least Squares data fitting and it was showed that presented approach is significantly faster (ratio of processing times depends on the number of measurement frequencies). Additional advantage of the proposed method is very low computation complexity (it is not iterative) so it can be easily implemented in portable and autonomous low-cost microcontroller-based systems for bioimpedance measurement and parameter estimation of the Fricke-Morse model in real-time.

The heart sound signal (heartbeat) recorded from normal subjects usually contains two separate tones, S1 and S2. In addition, an auscultation technique used to provide physicians with accurate and objective interpretation of heart sounds can be used to detect four sounds, namely, S1, S2, S3, and S4, during the heart cycle. In this project, we propose a technique to detect these four heartbeats effectively using the combination of multi-scale wavelet transform and Teager Energy Operator to increase the precision of the detection process. The purpose of combining TEO with Wavelets is to observe how different details obtained from the Wavelet Transform influence the Teager Operator success in detecting S1, S2, S3, and S4 heart sounds. The effectiveness of the proposed approach is evaluated in experiments related to different cardiac conditions, achieving 88 % accuracy for localization of S1 and S2, and 86 % accuracy for S3 and/or S4.

This research implements decision tree classifiers and artificial neural network to predict whether the patient will live with ovary cancer or not. Dataset was obtained from Danish Cancer Register and contains five Input parameters. Dataset contains some missing values and a noticeable improvement in accuracy was detected after removing them. Three features of the original dataset were shown to be the most significant: Mobility of the cancer, Surface of the cancer, and the Consistency of the cancer. The addition of the other two features (Size of the cancer and age of the patient) did not improve the results significantly. It was noticed that the patients with a cystic, but fixed and even cancer have always died from the ovary cancer. In contrast, the patients with uneven, but fixed and solid cancer have always survived the cancer. It is recommended to include more information about either the cancer or the patient to increase the chance of predicting the output of such patients.

The emergence of wearable low-cost wireless devices has allowed for continuous acquisition of physiological signals. Recently number of studies have applied these acquisition systems in different types of health monitoring. Since continuous elevation of stress hormones can have negative impact on individuals’ health, it is important to recognize and possibly prevent stress episodes in working environments. In this paper, we have tested if single-channel electroencephalography (EEG) signals can be utilized in assessment of different levels of mental workload and stress. Experimental study was conducted in laboratory settings with nine participants. In addition to EEG signals, we have acquired electrocardiogram (ECG) and electrodermal activity (EDA) recordings during all stages. Two scenarios are tested: first group of participants was introduced to only mental workload assignments, while second group was tested with mental workload and public speaking task as an stress inducing assignment. The experimental results show that EEG features have an acceptable separation ability between investigated states, where best classification accuracy, obtained between relaxed and high mental workload states, was 86.66%. Compared to only ECG or EDA features, EEG-based classification accuracy is higher in both scenarios, but lower in comparison with combined features from all three physiological signals.

This paper presents application of electroencephalography (EEG) measurement device for recording EMG signals from the arm muscles in order to generate motor shaft movements. System used for this experiment consists of electrodes primarily intended for use in electroencephalography, which are placed on person’s skin and connected to the simple EEG device. Recorded signals are forwarded to the PC in purpose of filtration using BrainBay software and later sent to the development board. Firmware in the microcontroller on this board regulates rotation of the stepper motor, whether clockwise or counterclockwise. This implementation enables real-time response to muscle contractions, thus moving the stepper motor.

Alzheimer’s disease is a neurological disorder that usually starts with aging. Alzheimer’s disease is a serious health and economic burden on governments, along with an increase in elderly population in developed and developing countries. There is no known cause of this disease and there is no treatment. For this reason, early diagnosis of the disease, socioeconomic and psychological outputs and medical treatments are still a hot topic investigated in the world. Magnetic Resonance Imaging is one of the medical imaging techniques that show the progression of Alzhiemer in brain. Brain deterioration and volume loss of the disease first begins with memory regions and then spreads to other brain regions. If atrophy is observed and detected by manual methods, it may not be seen due to user dependency, operator error and inexperience. For these reasons, automatic, numerical and atlas-based methods are being developed for the observation and capture of neurological diseases. In this study, 99 Alzheimer patients and 99 normal control MR images were analyzed using Voxel Based Morphometry, one of the numerical methods of atrophy observations in Magnetic Resonance Imaging. Losses in the brain were then produced as three-dimensional binary masks. Using these masks, normalized segmented, modulated normalized segmented, and normalized images that were stripped from the non-brain structures were masked. Histogram based first order statistical features were extracted in the masked areas. The efficany of this technique was statistically compared between Alzheimer’s and normal control. MR images have been downloaded freely from the OASIS database.

CBCT images suffer from acute shading artifacts primarily due to scatter. Numerous image-domain correction algorithms have been proposed in the literature that use patient-specific planning CT images to estimate shading contributions in CBCT images. However, in the context of radiosurgery applications such as gamma knife, planning images are often acquired through MRI which impedes the use of polynomial fitting approaches for shading correction. We present a new shading correction approach that is independent of planning CT images. Our algorithm is based on the assumption that true CBCT images follow a uniform volumetric intensity distribution per material, and scatter perturbs this uniform texture by contributing cupping and shading artifacts in the image domain. The framework is a combination of fuzzy C-means coupled with a neighborhood regularization term and Otsu’s method. Experimental results on artificially simulated craniofacial CBCT images are provided to demonstrate the effectiveness of our algorithm. Spatial non-uniformity is reduced from 16% to 7% in soft tissue and from 44% to 8% in bone regions. With shading-correction, thresholding based segmentation accuracy for bone pixels is improved from 85% to 91% when compared to thresholding without shading-correction. The proposed algorithm is thus practical and qualifies as a plug and play extension into any CBCT reconstruction software for shading correction.

Early detection and treatment opportunities for lung cancer is reduced the mortality of this disease. Chest radiography is one of the commonly used screening methods for the preliminary diagnosis of lung cancer. In this study, analgorithm fornodule detection in chest radiograph imageis presented. It takes into account the suspicious salient regions. Firstly, in order to enhance the image contrast, the CLAHE filter is applied. Then, local maximal regions are extracted by multi-scale approach based on optimum lifetime. Some of theseregions are eliminated by decision tree using the morphologic and the intensity features for detection and segmentation of candidate nodules. Finally, the texture features extracted from the segmented regions are classified by using RusBoost method. The method has been tested on the JSRT (Japanese Society of Radiological Technology) database images. Experimental results demonstrate that theproposed method achieves a very satisfactory performance for detection and segmentation of the suspicious salientregionsat the same time.

The task of counting colony forming units (CFUs) manually is repetitive, time consuming and prone to error. Many different approaches have been developed trying to automate this task aiming towards fully automated and reliable software for colony counting. This work presents a new approach to automated counting of CFUs based on histogram modeling using Gaussian mixture models.

The difficulties related to the sense of vibration could be characteristics of the specific neurological disorders, so there is a need for measurable and quantifiable information about its functionality. Currently used methods for testing the sense of vibration do not provide appropriate information, and new method of vibratory stimulation was introduced in the area of the neurophysiological research. Method provides repeatable and quantifiable information about the evoked cortical activity, but there was a need for information about the functional integrity of the whole vibratory sensory pathways. The result of this research was the electrode setup that provides information from the Erb’s point through the levels of the cervical spine to the contralateral sensory area at the cortex. Also, the setup consists only of four electrodes for each side of the stimulation (six electrodes all together, because electrodes positioned on the cervical spinal cord are common for both sides of the body), which reduce time necessary for preparation and allows better use for clinical purposes.

Automatic exposure control (AEC) techniques in computed tomography (CT) have been defined as automatic modulation of tube current in the x–y plane (angular AEC), along the z-axis (z-axis AEC) or both (combined AEC), according to the size and attenuation characteristics of the body region being scanned. These techniques should provide constant image quality while lowering the radiation dose to patients. Although AEC is an important feature of all modern CT units, standard methodology for quality control of AEC does not exist. Aim of the paper was to provide reliable quality control (QC) method for AEC techniques used in CT. Change of tube current during the CT examination happens only if the scan projection radiogram (SPR) shows different size and attenuation characteristics of the object being scanned. In order to maintain repeatability of the modulation we used standard polymethyl methacrylate (PMMA) dosimetry phantom, placed with flat side along the z-axis. After SPR was taken, phantom was removed, and CT solid-state detector was placed in the isocenter. Measurements were performed in axial mode, one slice only, for different positions along the z-axis. Dose rates measured in the isocenter, that are proportional to tube current, were found depending on the phantom geometry. In the phantom center the width of rectangle is the same as the diameter of the cylindrical phantom (32 cm), while height corresponds to the cylinder thickness (15 cm). Results show that during the rotation the current is highest when the tube is positioned at the x-axis, and lowest when tube is crossing the y-axis. However, when the detector is moved to position $$z = 14.1\,\mathrm{cm}$$, tube current (air kerma rate) does not change during the rotation. The methodology presented in this study could be used as a basis for defining the QC procedure for TCM. The results are consistent with the expected outcomes.

Unobtrusive data collection in a smart home environment can help with performing automated health monitoring and assessment. For instance, changes in mobility patterns which can be related to changes in cognitive abilities or an early sign of depression. In this paper, a system, using paired passive infrared (PIR) sensors at each entry of the house, observes the collective activities of a single resident individual, to model his or her mobility patterns. This system is designed in a manner that, while ensuring reliability and accuracy, reduces possible impacts on the individual’s privacy and does not add additional complications to the installation phase.Based on a mobility pattern data collection over a period of three weeks in our smart home testbed, analysis of well-known medium access control (MAC) protocols applicable to the scenario under study is reported. While most of the researches have simulated the existing MAC protocols, we focus on using a real system and traffic pattern. In this research, we set up a testbed which employs PIR sensors to accurately record movements and the activities of our case study for 21 days. Furthermore, to emphasize on the inaccuracy of simulation analysis, we compare our collected data to three suitable MAC protocols, namely X-MAC, RI-MAC and A-MAC, with respect to duty cycle and packet delivery ratio. The acquired results indicate that, by applying real data, the performance of MAC layer protocols is similar. While the simulation analysis of A-MAC shows a higher duty cycle rate to RI-MAC and X-MAC protocols by 16.8 and 23.5 percent, respectively, our real data does not show a similar performance of the three MAC protocols. Additionally, we apply the well-known CASAS project dataset to run further analysis, which shows a similar output to our reported results.

This paper presents the proposal of integrated software system for simulation and GIS visualization (Geographic Information System) of accidents caused by emission of hazardous gases from industry plants or storage facilities. Two software solutions for modeling, simulation and visualization of the propagation of hazardous gases through the simple (XY) and complex (XYZ) terrain are proposed. Software solution named “XY plume” is based on the use of free and reliable ALOHA and SCREEN3 software’s for modeling and simulation of the dispersion of hazardous gases. Proposed solutions use Google Earth, Google Maps and Open-Street Maps Web GIS browsers for visualization and marking. When estimating the zones of air pollution, different types of sources broadcasting are taken into account as well as meteorological conditions at the site of the incident. Calculated danger zones are displayed on Web GIS browser and used in risk assessment and action planning, according to the adopted plans to react in crisis situations. As a mechanism for connecting the dispersion models and Web GIS browsers, Keyhole Markup Language (KML) protocol is used because it can be activated via any Internet browser. In this way, the simulation results can be used over any computer that has an internet connection as well as through smartphones, tablets, and other devices that have mass application.

Medical devices with measuring function are regularly used in healthcare systems all over the world with the aim of prevention, diagnosis, and treatment of diseases. Considering the importance of these devices in daily activities of medical professionals and impact of their measurements on the health of patients, safety and accuracy of their measurements is becoming the topic of interest. Numerous international guidelines define how healthcare institutions should perform these conformity assessment but in some countries, where those guidelines are not adopted, it is necessary to implement directives of new approach for various groups of medical devices. Directives of new approach in terms of medical devices and their conformity assessment can be implemented in the area of legal metrology, as it is done in Bosnia and Herzegovina. This paper presents achievements and activities of Institute of Metrology of Bosnia and Herzegovina (IMBIH), the competent state authority for metrology in Bosnia and Herzegovina, in the area of legal metrology for the particular group of medical devices with measuring function. These achievements and activities refer to the adoption of appropriate legislation for type approval, verification, and creating an adequate legal framework for controlling medical devices after they are sold on the market. In addition, considering complexity and variety of medical devices related to measuring characteristics, and also due to the problem of inadequate or not defined traceability routes, the medical devices will continue to be in focus of metrological practice and science. Establishing the comparative approach to the type approval for these devices in the area of the legal metrology is the final aim.

Chronic kidney disease (CKD) is a global public health problem, affecting approximately 10% of the population worldwide. Yet, there is little direct evidence on how CKD can be diagnosed in a systematic and automatic manner. This paper investigates how CKD can be diagnosed by using machine learning (ML) techniques. ML algorithms have been a driving force in detection of abnormalities in different physiological data, and are, with a great success, employed in different classification tasks. In the present study, a number of different ML classifiers are experimentally validated to a real data set, taken from the UCI Machine Learning Repository, and our findings are compared with the findings reported in the recent literature. The results are quantitatively and qualitatively discussed and our findings reveal that the random forest (RF) classifier achieves the near-optimal performances on the identification of CKD subjects. Hence, we show that ML algorithms serve important function in diagnosis of CKD, with satisfactory robustness, and our findings suggest that RF can also be utilized for the diagnosis of similar diseases.

One of the projects of the Health Technology Assessment Division of the International Federation for Medical and Biological Engineering is a global survey on biomedical engineering (BME) professionals in health technology assessment (HTA).The data used in this work were derived from the main findings of the 2015 Global Survey on Health Technology Assessment by National Authorities carried out by the World Health Organization, and from the web data provided by the Croatian national authorities or Official Gazette publishing Croatian legislation.Globally, the numbers and proportions of professionals grouped as biomedical and/or clinical engineers, lawyers and librarians/information specialists involved in HTA reporting and decision making appear unacceptably low, even in case of medical devices (~20%). The situation at the national level seems to be worse.Crucial importance of medical devices and other substantially engineering-related health technologies in modern biomedicine and healthcare urges further surveying on BME professionals in HTA.

This paper presents the development of an Expert System for the classification of metabolic syndrome (MetS). Two-layer feedforward Artificial Neural Network (ANN) with sigmoid transfer function is used for MetS classification. In accordance with international guidelines NHBL/AHA, classification is performed based on following input parameters: waist circumference, blood pressure, glucose level, HDL cholesterol and triglycerides. Samples for training of developed Expert System are obtained from 1083 patients at hospitals in Bosnia and Herzegovina.Testing of developed system is performed with 300 samples, also acquired from patients in hospitals in B&H by medical professionals. Out of 300 samples, 155 samples were of MetS while the rest was of healthy subjects. Developed Expert System correctly classified 283 MetS samples, therefore the sensitivity of 96% is achieved and specificity is 92,7%.

In the past few years, developing of computer-aided systems for disease classification has been investigated more extensively. Medical professionals use these systems as assistance in diagnosis since they perform the diagnosis based on larger, more complex set of new and previously stored information. Those computer-aided systems are equipped with graphical user interface that makes application in everyday situations more convenient. Disease classification in most computer-aided systems is based on expert systems. Beside the Artificial Neural Networks (ANNs), fuzzy logic (FL) or some other tools are often used for this purpose.This study presents the results of disease pre-classification process and determining the need for conducting respiratory function tests such as spirometry (SPIR), Impulse Oscillometry (IOS), or Body plethysmography and running the Fuzzy Logic – Artificial Neural Network (FL-ANN) Expert System for classification of respiratory diseases. This pre-classification algorithm optimizes time resources as well as reduces the costs of medical device use needed for testing of patient and costs of medical professional attending the measurement. Questions and symptoms used in pre-classification are based on Global Initiative for Asthma (GINA) and Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. The pre-classification algorithm is validated on 5000 reports acquired from subjects prospectively enrolled in the Hospital in Sarajevo during the period of two year and CareFusion Database for the last 10 years. Sensitivity of 97.26% and specificity of 90.74% is achieved. It is shown that saving around 97% on pulmonary functions tests can be achieved by introducing these automated systems in everyday practices.

The aim of the study was to investigate the efficiency of artificial neural networks and docking studies in prediction of antimicrobial activity for new compounds. For that purpose, two multilayer neural networks with feedforward architecture were developed. Also, docking studies were performed to investigate the hypothetical binding mode of the target compounds. A series of 2,2,5,5-tetramethyl-9-aryl-3,4,5,6,7,9-hexahydro-1H-xanthen-1,8(2H)-dione derivatives have been previously synthesized, characterized and evaluated for in vitro antimicrobial activity against Escherichia coli and Candida albicans strains. By comparing results of in vitro investigation, new 2,2,5,5-tetramethyl-9-(3,5-dibromophenyl)-3,4,5,6,7,9-hexahydro-1H-xanthen-1,8(2H)-dione possessed better antimicrobial activity against tested microorganisms than previously synthesized derivatives and these results also correlated well with results of docking studies.

The cell cycle is an ordered sequence of coordinated biological processes that enable cells to grow and divide, to check for certain abnormalities whenever it is appropriate, to regulate the different stages of growth and division in the predefined order, and to respond to DNA damage and other dysfunctions by arresting progression through the cell cycle so that to allow the regulators to repair DNA damage and recover from dysfunction before DNA is completely replicated. Mathematical and computational modeling and simulation is a well-known approach to explore biological systems. The main idea behind this approach is to create the closest approximation of a biological system based on wet lab results, and predict its dynamic behavior through measuring the amounts of biological components. Mathematical and computational approaches implemented to cell cycle regulation have the following benefits. Firstly, it makes possible to provide a detailed qualitative and quantitative structure of the biological system describing the cell cycle regulation. Secondly, modeling allows us to conjecture a hypothesis regarding the biological system and then check consistency of the hypothesis to desired deep by extrapolating the parameters involved into the model.

This paper presents a system that enhances the effectiveness of a national vaccination planning and dispensing system for countries where the Government has been spending huge resources with not much success in out reaching vaccination programs to remote places and to all inhabitants. This study focuses on finding the shortcomings and gaps being faced during vaccinating children in Pakistan. The case study for Pakistan has been done by performing requirement engineering and considering many factors relating to people behavior and attitude and based on the study designing a system by using Information and communications technology as an enabler to address all gaps and shortcomings while ensuring human factors are tackled by the technology. The design guarantees proper scheduling, execution and monitoring of every child’s vaccination schedule as well as events generation to ensure it is enforced right from its birth hence resulting in clean sweep of infectious diseases and making Pakistan an example for other developing countries to follow. The system also gives visibility to the decision makers for gauging the efficacy of the system. It helps them to take managerial decisions and steps to ensure that vaccination programs are executing with maximum benefits in response to the immunization improvement program.

The advancement of embedded system technologies, sensing techniques and wireless technologies provide new possibilities to monitor human activities at all times. This paper focuses on Heart Rate Data acquisition and management as a part of the Stroke Center project which is currently being developed. Non-intrusive wearable heart rate sensors monitor patients and detect abnormal situations. Data is analyzed and sent in real time in order to provide necessary help when it is needed. The Stroke Center framework is briefly described in this paper with guidelines for future work.

Measuring the customer satisfaction is one of the most important aspects for every successful enterprise trying to improve its service quality, so accumulating reviews is highly encouraged. However, as the number of reviews expand it is crucial to develop effective sentiment analysis systems capable of classifying the comments to accomplish further analysis. This is one of the rare studies analyzing health service contentment, especially in Turkish. Positive and negative comments collected from patients were used to train and test a classification system by using machine learning methods such as Naïve Bayes, Support Vector Machine (SMO) and J48 tree algorithms, resulting in instantaneous and high average prediction rates varying between 90.4% to 95.8%.

This paper demonstrates an e-medical test recommendation system based on the analysis of patients’ symptoms and anamneses. The exact test selection for a specific patient can be time consuming and error-prone due to the huge amount of information to be considered like: the number of tests, patients, long working hours, exceptional cases, etc. The redundant or missing tests can cause serious loss of money, time and more seriously delay in the initiation of the therapy. The study aims to provide a fast and cost effective system for the medical experts and patients. The data are collected from the patient records of a private hospital, preserving anonymity, from all departments. Only the internal medicine department data are utilized. The patients’ age, gender and the words used in the anamneses and symptoms as plain text are the input for the system. The texts are analyzed and various methods have been applied for selecting the effective words for recommending a specific medical test. These terms, along with the demographic information, are used as the features of the well-known machine learning algorithms of WEKA [5], namely Sequential Minimal Optimization (SMO), J48, Random-Forest (RF), Bagging (Bagg), ADTree (ADT) and AdaBoostM1 (ABoost). The number of medical tests that are applicable in the hospitals is too high, therefore only 20 most frequently required ones are selected. The promising results of the study indicated that the symptoms given as plain text can be efficiently utilized by the experts for medical test selection.

Hypertension is defined as values ≥140mmHg systolic blood pressure and/or ≥90 mmHg diastolic blood pressure. Pharmacological and non-pharmacological therapy is used in treatment of hypertension. Non-pharmacological therapy (lifestyle changes) is extremely important and represents the foundation for the treatment of hypertension. Pharmacological therapy refers to the administration of antihypertensive drugs, which, however, includes a large group of drugs. In internist everyday practice, in revisions of patients therapy, and in the work of physicians, family medicine specialist, on a daily basis a need for modification of therapy occurs (primarily due to unregulated pressure, then due to side effects that can happen in use of certain treatment, or because of drug interactions, which can lead to poor quality of treatment). In this modification of therapy or switching one drug to another there is a need for knowledge of equivalence doses of certain drugs. Individualization of therapy for the patient is a trend that will certainly in future even more come to the fore. Number of mobile clinical decision support systems is on the rise due to availability and ease of use. The antihypertensive therapy dosage calculator would be modeled as a cross platform mobile application targeting the two predominant mobile platforms, iOS and Android.

Wireless communication is becoming a part of our life at every step. But widespread use in medical applications is yet to come. We are developing a wireless communication system based on 802.15.6 MAC and 802.15.4 PHY for use in transmitting ECG data from a remote patient monitoring device which is used for home based telemedicine applications. The paper concentrates on explaining the stack program development phases of the standard IEEE 802.15.6 and its flexible access features. It is believed that the subjected standard is going to provide a medical data highway in its reserved bands.

Modern medical breakthroughs and general improvements in environmental and social conditions have raised the global life expectancy. As the world’s population is aging, the incidence and prevalence of chronic diseases increases. Dramatic increase in the numbers of chronically ill patients is profoundly affects the healthcare system. Care at home provides benefits not only to patients but also the community and the health care providers. A telemedicine system utilizing today’s information and mobile communication technologies plays a crucial role in providing care at home. Currently, diverse telemedicine projects are progress in the most countries. A telemedicine project is supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK) under Grant 114E452in Turkey. This project aims end to end remote monitoring of patients with chronic diseases such as heart failure, diabetes, asthma, and high blood pressure. A clinical decision support system integrated to telemedicine improves prognosis and quality of life in patients. The mainstay of a decision support system is early detection of important clinical signs and prompts medical intervention. Cardiovascular diseases are the leading cause of death globally. People with cardiovascular disease need early detection. An effective decision support system is needed to detect ECG arrhythmia before a serious heart failure occurs. One of the aims of the project is to develop decision support system which will detect whether a beat is normal or arrhythmia.The ECG signals in MIT-BIH arrhythmia database and Long Term ST Database are used for training and testing the algorithm. A total of 103026 beat samples attributing to fifteen ECG beat types are selected for experiments in MIT-BIH arrhythmia database. 103026 RR intervals with ST segment change were selected from the Long Term ST Database. ST segment changes detection is just based on the signal between two consecutive R peaks. The features are obtained from Wigner-Ville transform of this signal. The classification algorithms provided by the MATLAB Classification Learner Toolbox were tested. The Cubic SVM achieved best results with accuracy of 98.03%, sensitivity of 98.04%, specificity of 98 % and positive predictive value of 98%.

This paper presents a framework for the prediction of naphthalene concentrations in the liver and lung compartments of a micro cell culture analog apparatus (μCCA) using a microcontroller system based on an Artificial Neural Network (ANN). The system can be used to simulate organ and circulatory system reactions in terms of residual naphthalene concentrations before conducting experiments on a μCCA. The system is implemented as follows: a keypad which is used to input the quantities of inhaled air (naphthalene), a microcontroller for processing and data prediction, a LCD to display the predicted values. The ANN, previously trained in MATLAB, was transferred to the microcontroller in order to obtain predicted naphthalene concentrations in the liver and lungs. The complete framework is described with guides for future work.

In this paper development of Artificial Neural Network for classification of prediabetes and type 2 diabetes (T2D) is presented. For development of this system 310 samples consisting of information about Fasting Plasma Glucose (FPG) and blood test called HbA1c were used. All samples were obtained from several healthcare institutions in Bosnia and Herzegovina, and diagnosis of prediabetes, T2D and healthy patients in this dataset were established by medical professionals. Two-layer feedforward backpropagation network with 15 neurons in hidden layer and sigmoid transfer function, used for classification of prediabetes and T2D in this paper, was trained with 190 samples.Testing of developed neural network was performed with 120 samples for validation also obtained from healthcare institutions in Bosnia and Herzegovina. Out of 120 samples, developed network was accurate in 94.1% cases for the classification of prediabetes and in 93.3% cases for classification of T2D.

This paper aims to use signal processing techniques to identify biophysical events using audio signals. The processing technique proposed is a combination of the mel frequency cepstral coefficients (MFCC) used as features, independent component analysis (ICA) and principle component analysis (PCA) algorithms to separate sources and noise. It was found that compressing the data into the energies of 26 filter banks mapped to the mel frequencies, sufficient descriptive information was conserved as validated by visually identifiable source signal patterns. Subsequently performing PCA isolated global background noise to an individual component. Further, by performing ICA, components contained independent and visually identifiable patterns that correlated to events associated with heart rate, squatting motion and involuntary abdominal movements. This componentized feature space provides an optimized source for building a discriminant function for the classifier used in the machine learning algorithm to provide simultaneous and automatic classification of these biophysical events.

In this study, the diversity performance of microstrip patch antennas mounted on the chest and the back of a person is investigated in static and dynamic indoor environments at ISM (2.4-2.5 GHz) and medical body area network (2.36-2.4 GHz) bands. Power received by the radios worn by the person while standing and walking is recorded and compared. In addition, antennas are simulated on a human body to study the effect of the human body. The work was done as part of a remote patient monitoring project, and hence the effectiveness of the antenna diversity in the indoor data communications and the impact of the human body on the quality of the communication linked were studied as well.

This paper presents an approach for detecting characteristic points in PPG (Photoplethysmogram) signal for the purpose of HRV (Heart Rate Variability) analysis. From IBI (Inter Beat Intervals) distribution several statistical parameters are extracted. For the purpose of comparison the same distribution and parameters are extracted from ECG signal by most used Pan-Tompkin’s algorithm. Using experimental set of data, under different conditions (spontaneous, controlled or assisted ventilation) and performing tests on the signals from the database which is consisted of patients of various ages, the high correlation in terms of statistical errors has been achieved, mean square error less than 100 ms in 89.19 % of calculations, error in calculating HRV less than 5 beats/minute in 91.89 % of tests. The proposed method provides additional advantages because it can be used for simplified measurement and signal processing, which can include easy hardware-software implementation and low cost. After the introductory notes, processing principles, verification and comparison procedure as well as preliminary results are presented.

Modern technologies for evaluation of spinal deformities are based on assessment of the surface geometry of the torso in different ways. 3D scanning and 3D reconstruction using low cost Kinect sensor can contribute in rapid and low cost elaboration of a 3D mesh of the patient’s back. This paper describes the instrumentation, technique and the results of a Kinect based system for screening of scoliosis and kyphosis. The system proposed in this investigation uses infrared ray technology to evaluate the torso surface of patients. This work discusses the advantages and limitations of the proposed scanning system. Experimental results demonstrated that the low-cost depth sensors can produce accurate 3D models when combined with specialized software. Due to numerous transducers, the Kinect sensor may be used in a lot of medical bioengineering applications.

Patients with Locked-in Syndrome are unable to move, apart from certain eye movements and perhaps one or two other muscles; this may be due to Amyotrophic Lateral Sclerosis, nerve cell damage or a stroke, among other reasons. The condition normally results in the patient losing the ability of verbal communication. The task at hand was to develop an EMG switch that would generate outputs based on the detected muscle activity. The existing switch achieved substantial success, giving binary YES/NO outputs. The investigation sought to consider three limitations of the existing system: the sensitivity of the switch to the smallest possible signal amplitude; the ability of the switch to detect signals of differing magnitudes; the ability of the switch to detect signals of differing velocities. Significant progress was made regarding the first two matters. By using an adaptive threshold based on moving averages and upper bounds defined by data spread, the algorithm was able to detect large and small motions to an average of 91.8% accuracy, 95.8% precision and 95.9% recall - building on the previous algorithm. Regarding detecting signals of differing magnitudes, set threshold bands were show on screen as visual prompters to appear at different levels, which the patient/user would use to aim for different threshold bands to generate a number of different outputs. With training, a user would be able to communicate more effectively. Future research should seek to continue improved the solutions to the first two challenges, and make progress on signal velocity detection.

P300 potentials are involuntary responses which were elicited when a subject recognizes a target item among a group of irrelevant items. In order to determine the target item that the subjects intend to select, multiple ERP responses for each stimulus must be evaluated. The number of intensification sequences required to select a target item may vary among the subjects as well as sessions which a subject participated in. Therefore, instead of using a predetermined number of intensification sequences, it should be determined automatically at the moment of selection. This paper proposes a dynamic stopping algorithm to determine required number of intensifications sequences. The algorithm uses the optimal operating point of the ROC (Receiver Operating Characteristics) curve to determine the threshold values. The proposed algorithm was tested on two different datasets which use row/column (RC) paradigm and region based (RB) paradigm. Dynamic stopping algorithm significantly improved SPM (symbol per minute) on both datasets by reducing number of intensification sequences and ratio of erroneous selections. Because it does not require to select two of the selections at same number of intensification sequences, RB paradigm provides more flexible, rapid and accurate BCI systems.

Candida albicans, the polymorphic fungus that colonizes mucosa of mouth and gastrointestinal tract, is a member of normal microbiota. However, under special circumstances, this microorganism can switch from harmless, commensal into invasive, opportunistic pathogen, causing even life-threating infections in humans. Aspartyl proteinase is an enzyme that acts as one of the cruical virulence determinants of Candida albicans and is involved in tissue degradation and dissamination of infection characteristic for oropharyngeal or vaginal candidasis. In our study we investigated influence of different agents, metals and drugs, on fungal excretion of aspartyl proteinase. We could see that already know degradation of human proteins caused by microbial proteinases can be enhanced due to stimulatory effect of iron metal ions and analgesics. These agents significantly increased secretion of aspartyl proteinase and enhanced virulence mechanism of Candida albicans.

The application of computer skills and technologies in modern business is essential in modern society, therefore different methods and algorithms are used for the business optimization. This paper primarily focuses on solving the transportation problem of the linear programming for the purpose of the transport optimization, which ultimately leads to the competitive advantage for any institution which performs any type of transport as a part of its business. Therefore, specially implemented Java program for the purposes of pharmaceutical institutions will be presented. The need to optimize the product transport from the producer to the consumer is of a great importance for any company, including pharmaceutical one. The aim for solving the transportation problem is the application of algorithms over real data from the appropriate database of the merchandise management in order to optimize the transport of medicines and other pharmaceutical products from the factory to pharmacies or other institutions.

The coumarin derivatives are quite interesting objects for both synthesis and pharmacological screening. Major problems in medicine today include resistance to drugs, where a number of enzymes and receptors important for the tumour cell cycle progression may be considered as potential targets for new drugs.Presented study was aimed to evaluate in vitro antiproliferative effects of previously synthesized benzylidene-bis-(4-hydroxycoumarin) derivatives and fused benzopyranocoumarin derivatives. Compounds were tested on HeLa, SW620, MiaPaCa-2, MCF-7, HepG2 and WI-38 cell lines. The most potent compounds were subjected to molecular docking simulations in order to reveal binding modes and mechanism of interaction of synthesized compounds with target receptors. Furthermore, physicochemical properties included in Lipinski’s rule of 5 and polar surface area were calculated to determine compounds’ solubility properties and their appropriateness for oral intake in humans.

The modernization of IT leads to an improvement in numerous segments of the pharmaceutical activities. Thus, new field, pharmaceutical engineering was formed. Drug design is segment of it. Within that, the artificial neural network (ANN) possibility to determine the most suitable drug molecule for a transdermal administration is tested.Transdermal preparations industry is predicted to be worth cca 81.4 billion US dollars by 2024. This approach to drug design should be increasingly used due to convenience and cost-effectiveness of the method.The ANN was developed and trained by inserting over 500 dataset. The set included physiochemical parameters of drug molecule (molecular mass, melting point and partition coefficient), pharmacokinetic parameters (elimination half-time, dose and bioavailability) and biological parameters (skin permeability and coefficient of skin permeability). These parameters endeavored drug classification in one out of two success categories, respectively whether transdermal administration is possible or not.Various types of ANN were tested in order to acquire best accuracy and reliability. Types of ANN that resulted with accuracy above 95% have been considered. Sensitivity analysis of output variables related to input, suggested that certain parameters are more significant. Lastly, selected ANN had highest accuracy and least input parameters. Effect of overfitting was avoided while training selected ANN with highest accuracy.Based on the results of this study, ANN could be successfully used for predicting passive absorption of drug molecule through transdermal application. In addition, ANN could be used in order to facilitate processing large number of data. Hence, predicting mode of application for drug administration.

Due to dynamic maturational changes in neonatal life, changes in pharmacokinetic (PK) and pharmacodynamic (PD) processes of drugs administered to neonates are expected. However, children are mostly treated off-label, i.e. without testing the drug in children but based on the extrapolation of data from adults. For the optimisation of dosage regimens in neonates, besides Therapeutic drug monitoring (TDM) and a Bayesian feedback algorithm, population PK approach became relevant. Population PK modeling is a stepwise approach with building of structural and covariate models, model evaluation and simulations resulting in estimation of the population mean values of PK parameters such as clearance and volume of distribution, their inter- and intra-individual variabilities, covariates as well as on simulation-based optimised dosing proposals. The relevance of those approaches in overcoming gaps between realistic and feasible in-practice situations while performing PK studies in children, and taking into account ethical requests to minimise the number of studies in children and to minimise the number of children recruited to studies is also recognised by the authorities. In this article, we aimed to emphasise the importance of the research and of the population PK approach in the improvement of rational antibiotic therapy in neonates and to illustrate this with some specific compounds. For this reason, we gave a short overview of the population PK studies of the most frequently used antibiotics in European neonatal intensive care units. As final results of performed population PK analyses, optimised dosing regimens were proposed for rational antibiotic treatment and prophylaxis of neonates.

INTRODUCTION: Pernicious anemia is an autoimmune megaloblastic and macrocytic anemia, characterized by a deficiency of vitamin B12 and the absence of internal factors in gastric juice. In this type of anemia values of red blood cells and hemoglobin are reduced, and it is followed with a slight decrease in the number of leukocytes and platelets, and granulocytenucleus hypersegmentation. Observations of the peripheral blood smear clearly show: microcytosis, hypochromia, anizocytosis, poikilocytosis.Iron deficiency anemia (IDA) is a condition in which blood lacks adequate healthy red blood cells due to insufficient iron. In the peripheral blood smear of IDA patients, following is clearly observed: microcytosis, hypochromia, anizocytosis, poikilocytosis.The number of red blood cells is reduced, disproportionate in relation to the reduction of hemoglobin, while the values of leukocytes and platelets is usually normal.AIM: The aim of this research is to investigate the association of hematologic parameters and inflammatory markers in patients with these two anemias.MATERIALS AND METHODS: The study used data of laboratory tests of 100 patients with anemia, of which 50 with anemia due to iron deficiency (anemia hypochromic), and 50 with pernicious anemia. The study involved data of adult patients whose hemoglobin level is below 138 g /L, and the value of the red blood cells line- red blood cells, beneath 4,30x1012/L.RESULTS: The value of leukocyte and platelet counts were statistically significant (p<0.001), but only in IDA group of patients.Differences in the number of red blood cells and hemoglobin concentration were not statistically significant in any of the groups. Statistically significant differences have been detected between the two groups of patients (p<0.0005), when it comes to values of neutrophils and lymphocytes. The correlation coefficient between MCH and CRP, and fibrinogen revealed a good negative correlation (MCH and CRP: r = -0.561,p<0.01; MCH and fibrinogen: r = -0.652, p<0.01).CONCLUSION: In the group of patients with IDA concentration of CRP was significantly higher compared to patients with other groups, which confirms the importance of CRP as a marker of inflammation. On the other hand neutrophil to lymphocyte ratio (NLR), had no correlation with either the parameters of anemia, and is generally the worse indicator of disease. NLR compared to CRP is a better biomarker in postoperative inflammation, while CRP may be a marker of decisions with preoperative patients.

The ABO and Rh blood group are the most important systems with various distributions reported for different populations. The ABO and Rh are known also to be associated with various diseases. Obesity is a complex chronic disease involving environmental, genetics, physiologic, metabolic, behavioral, and psychological components. The present study is aimed to explore the association and distribution of the ABO/Rh blood type and the risk of hypertension and obesity among students population. The study group consisted of 100 examinees, 14 males and 86 females, students aged 18 - 23. The blood group A was found to be the most prevalent (46 %), while the blood group AB was found to be the least prevalent (6%). The highest average value of the BMI was found in subjects with the blood group AB/Rh+ 22.36 ± 2.49 kg/m2 where the lowest value was in the blood group B/Rh+ 20.13 ± 2.64 kg/m2. The highest average value of systolic blood pressure was measured in subjects with A/Rh- 138.88 ± 16.63 mm Hg, while the lowest was in the blood group B/Rh- 118.50 ±7.55 mm Hg.

Type 2 diabetes (T2D) as a multifactorial disease is characterized not only by chronic hyperglycaemia but also with defects in lipid and protein metabolism. These defects impact the utilization of glucose and non-esterified “free“ fatty acids (NEFA) by muscle, liver, and adipose tissue. Free fatty acids (FFA) represent an important link between obesity, insulin resistance, and T2D. Eleveted plasma concentration of FFA (especially saturated FFA) is associated with impaired insulin secretion and sensitivity and glucose intolerance.The major objective of the present study was to investigate association of plasma free fatty acid profile in Type 2 diabetic subjects with different control of glycemia. This study involved 40 patients with T2D and 40 healthy subjects. Preparation of samples for FFA analysis was done by extraction and methanolysis of plasma lipids while detection and quantification of FFA concentrations was done by gas chromatography/mass spectrometry. Other biochemical analyses, including glucose, glycated hemoglobin (HbA1c), cholesterol, and triglycerides were done according to standard IFCC methods. A significant difference between T2D and control subjects was demonstrated only for palmitic acid (C16:0). There was a significant correlation of C16:0 with HbA1c levels (p<0.001) in patients with both adequate and poor T2D control. Also, a significant correlation was obtained at a level of plasma C18:1(p<0,05) and HbA1c level, only in patients with inadequate diabetes control. Thus, our data suggested that palmitic fatty acid (C16:0) and (C18:1) could serve as a potential biomarkers in optimal T2D management.

Vranac is very important grape variety within Montenegrin autochthonous assortment and it is one of the most significant for viticulture and winemaking sector in Montenegro. Grape of this variety is used for production of top quality red wine which is much appreciated at domestic and foreign market. Old grape varieties that have been cultivated for a long time on a specific area, such as Vranac, are characteristic by their heterogeneity in term of manifesting their features that gradually lead to degradation of grape variety. Because of that, within those appreciated grapevine varieties, there was a need for clonal selection in aim of certain vines separation which have positive mutations of some economically important traits. Work on clonal selection has started in 2004 in order to separate the best vines within population of grape variety Vranac. During multi-year (2004-2014) work on clonal selection of grape variety Vranac in Montenegro it was selected and recognized seven clones of this variety (Vranac clone 1, Vranac clone 2, Vranac clone 3, Vranac clone 4, Vranac clone 5, Vranac clone 6 and Vranac clone 7). Paper presents agro-biological, economic and technological features of Vranac clones comparing to population of variety. Selected clones surpassed population of variety in some of parameters of yield and grape and wine quality and based on that were recognized.

Angiotensin I converting enzyme (ACE) gene, as a component of Renin-Angiotensin System (RAS), regulates blood pressure as it converts somatic isozyme Angiotensin I into physiologically active peptide Angiotensin II and simultaneously brakes down bradykinins. Over 100 polymorphisms are reported for ACE gene. Most of these polymorphisms having no phenotypic effect relay the attention towards polymorphisms based on insertions (I) or deletions (D) of a 287 bp Alu repeat sequence in 16th intron. There are three possible genotypes for the stated polymorphism: DD, DI or II. There have been a lot of studies searching for direct associations between ACE polymorphisms and performance phenotypes along different sports requiring power or endurance. The previous experiments are based on the performance criteria but direct associations of ACE polymorphisms are not fully understood until today. We believe different approaches may aid scientist to plot the big picture. A sample population of 101 individuals from Bosnia and Herzegovina contributed to sample pool of the initial project. Buccal swabs from 101 samples were collected along with a phenotypic structure and environmental characteristic survey which was filled by each individual himself/herself. Genotypes of the individuals were obtained after isolation, amplification and gel electrophoresis of biological samples collected as buccal swabs. A total of 165 artificial neural network (ANN) models were developed considering the input parameters, possible genotype outputs, applied algorithm and sample size. The aim of developing various ANNs was to validate a possible ACE polymorphism genotype prediction algorithm based on phenotypic and environmental characteristics of individuals, in other words, without any biological testing. A two-layered feed-forward network, with sigmoid hidden neurons was designed to perform the classification of input data. Trainscg (Scaled Conjugate Gradient) activation function was used in hidden layer since classification of data was non-linear. All ANN models were trained with scaled conjugate gradient backpropagation. ANN models differing in the parameters has shown different accuracy in the results. Most outstanding result was observed in the ANN build composed of 2 distinctive layers with 500 neurons in the first and 3 neurons in the second layer. Trained with 70% of samples and verified with 15% of samples and validated with an additional 50 samples. Training set was composed of the following subject parameters; gender, eye color, hair color, height, weight, presence of hypertension in family and presence of cardiovascular diseases in family. The highest prediction accuracy was obtained as 86,6 % training score, 78,6 % testing score and 80,2 % overall score in genotype prediction for ACE polymorphisms. With further development of data collection and high resolution analysis, overall score could be boosted. Also, phenotypical data can be applied as markers of genotypes in ACE polymorphisms.

Autologous stem cell transplantation (ASCT) is an established treatment for patients with hematologic malignancies. The minimum CD34+ cell dose needed to ensure hematopoietic recovery following ASCT is 2x106 cells/kg. The aim of this paper is to prove that absolute number of cells (ANC) CD34+>=20,01x106/L in the peripheral blood is confirmation of successful collection. The study was a retrospective-prospective. We analysed 44 patients Myeloma Multiplex 23(33.3%), Hodgkin lymphoma 29 (42.0%), non-Hodgkin Lymphoma 17 (24.6%) with 69 apheresis conducted in the process of autologous stem cell transplantation at Haematology clinic KCUS in the period from April 2013 to October 2016. Patients were divided into two groups: collection of CD34+<2.0x106/kgand>=2.0x106/kgin one day.Independent variables analyzed were: CD34+cell dose in peripheral blood in one collection, age, gender and diagnosis. The average age of patients was 45 ± 16.03 years. Youngest patient was 18 and the oldest was 67 years. There were 52.3% male patients and 47.7% female.Collection of CD34+ <2.0x106/kg occurred in 20 (27.5%) cases and 49 (72.5%) had CD34+≥ 2.0. In the group with CD34+ ≥2.0x106/kg there were 91.8% with ANC CD34+ ≥20.01 x106 /l in peripheral blood. Only three collections of CD34+ >=2.0x106/kg had values in peripheral blood ANC CD34 + from 15.01 to 20.00x106 /l and only one collection ANC CD34+ between 10.01 and 15.00 x106 /l. Displayed difference is statistically significant p=0.0001. We used the c2 test, Kolmogorov Smirnov and Mann-Whitney U test. P<0.05 was considered significant. Successful collection is guaranteed at ANC CD34+ >= 20.01 x 106/L in the peripheral blood.