6th International Conference on Advancements of Medicine and Health Care through Technology; 17–20 October 2018, Cluj-Napoca, Romania

Recently, the fluorescence techniques have become increasingly important in medical diagnostics. Moreover, there is a growing need to introduce cost-effective and no time-consuming techniques for the investigation of various fluorophores in humans and animals with diabetes mellitus. In the studied literature, the newly diagnosis of diabetes mellitus and, subsequently, the risk of developing diabetes complications are reported to be correlated with the production of serum fluorophores pentosidine and retinol binding protein. As far as we are aware, there has been no study on the simultaneous fluorescence evaluation of pentosidine and retinol binding protein in biological fluids obtained from animals. In the present study, the emission intensity and levels of serum pentosidine and retinol binding protein were monitored in both healthy rats and rats with streptozotocin-induced diabetes. The results showed that the height of the peak at ~382 nm attributed to the presence of pentosidine in the serum, and the height of the peak at ~465 nm attributed to retinol binding protein in the serum were significantly higher in rats with streptozotocin-induced diabetes compared to healthy control rats. Also, their contributions to the total fluorescence of serum were significantly higher in rats with streptozotocin-induced diabetes compared to healthy control rats. Thus, fluorescence spectroscopy might be a reliable and useful technique that can be successfully applied in the evaluation and monitoring of serum pentosidine and retinol binding protein in both healthy rats and rats with streptozotocin-induced diabetes.

Diabetes mellitus registers an alarming increase globally, taking epidemic proportions. Diabetic neuropathies are considered the most prevalent chronic complications of diabetes, affecting up to 50% of subjects with diabetes during lifetime. Distal symmetric polyneuropathy (DSPN), a length-dependent injury of peripheral nerves is the most frequent type among diabetic patients. Small nerve fibers are the first affected in the natural progression of the disease and their early damage can be assessed using corneal confocal microscopy (CCM). We applied CCM to the study group of 90 patients with type 2 diabetes, to identify early signs of diabetic neuropathy, to stratify patients into classes of severity of diabetic neuropathy and to find potential correlation between clinical, metabolic parameters and diabetic neuropathy severity. In our study, 88.89% of the patients were diagnosed as having DSPN, 37.77% of them with mild form, 38.88% with moderate neuropathy and 12.22% with severe neuropathy. Patients with diabetic neuropathy had a significantly higher BMI (p = 0.04) and abdominal circumference, higher HbA1c (p = 0.36) and a higher total cholesterol (p = 0.43) compared with patients without DSPN. Also, the Toronto Clinical Neuropathy Score was significantly higher in patients with pathological changes of the sub-basal corneal plexus (p = 0.04). Patients with DSPN had a significantly longer duration of diabetes (p = 0.04) and a worse glycemic control, compared with patients without DSPN. The result of our study proved that CCM can be used as a reliable diagnosis tool for early detection of small nerve fiber damage, considering that corneal sub-basal plexus changes precede clinically detected peripheral nerve changes.

The benefit ultrasonography brings in medical practice when dubbed by a competent user is unquestionable. The following considerations support the assertion that the technique is non-invasive for the patient and the user, inexpensive, offering real-time relations as compared to other imaging and high performance techniques such as CT and MRI. In our clinical study, the four patients selected were representative for the above mentioned conclusions, being hospitalized and diagnosed sonographically with: tissue hematoma, pseudoaneurysm, arteriovenous fistula and venous thrombosis. After discharge, patients were clinically and sonographically monitored after 1, 3 and 6 months. The technique has also imposed a choice of treatment appropriate to each individual case, namely a conservative treatment for the patients with hematoma, pseudoaneurysm and arteriovenous fistula. For the patient with venous thrombosis, the prescribed treatment was medical. A surgical treatment (excision and ligation) for the pseudoaneurysm was also discussed. After a 6-month surveillance and delay, thrombosis was performed. We mention that the prognosis is also favorable after a surgical treatment when the evaluation and timing are correctly chosen.

Laboratory analyses of body fluids for the determination of disease-signaling biomarkers is an important stage of the diagnostics procedure. Although blood is recognized to provide the most reliable diagnostics data, blood collection is an invasive procedure and is perceived with reluctance by many patients. Therefore, the presence of disease-signaling biomarkers in other body fluids is investigated. This paper proposes the block diagram of a hybrid salivary sensor which correlates optoelectronic sensing with electrochemical sensing. Saliva is indeed a preferred body fluid for sampling, however it may also contain other compounds, as for example oropharyngeal mucosae, blood, etc. In the context of the hybrid salivary sensor, this paper investigates two solutions for the implementation of an optical salivary sensor for the identification of blood in the saliva. In the proposed solutions, blood is identified by color, rather than by chemistry. Therefore, pure optical means can be used, making the implementation in the shape of a side polished fiber straightforward. The novelty of this work consists in the employment of a fluorescent optical fiber for the construction of the fiber optic sensor. A laboratory proof of principle validates the proposed solutions.

Present paper is based upon a thorough analysis using specific devices in the Medical Engineering Laboratory meant to study the influence of handling various weights on the postural balance and implicitly on the health conditions. The weight was handled in different positions of the weight and it was lifted either by bending the body and keeping the legs straight or by bending the knees. The imbalance was determined by analyzing the aspect of the stability area using a Kistler force platform.

In this paper we present a report on the use of thermographic imaging techniques as a monitoring tool in newborn respiratory rate. The basis of this type of monitoring is the processing of real-time thermographic images. This contactless monitoring method it is absolute necessary because it is designed to monitor a very fragile category of patients: premature new born babies. Our biomedical signal of interests it is represented by the spontaneous breaths of the newborn. In the present study we demonstrate that the respiratory rate of the preterm newborn can be monitored based on the analysis of temperature changes that occurs in the anterior nasal area (nostrils).

Monitoring vital signs is a must in Neonatal Intensive Care Units. The objective of this work is to design and implement a neonatal pulse oximeter in an innovative form, easy to use in NICU (Neonatal Intensive Care Unit) or by parents at home, at an affordable price. Pulse oximetry is a method to measure oxygen saturation of blood (SaO2) and heart rate (HR); these parameters indicate the assessment of acid-base balance, if breathing is performed in an efficient manner, and if cellular metabolism is effective. For premature newborns or newborns on term the oxygen saturation decreases in case of intracranial hemorrhage, which is the major complication of a newborn, respiratory insufficiency due to insufficient development of the lungs, associated with respiratory pathology and heart failure. This is the reason why we designed an innovative pulse oximeter- that we called P-SOCK.

The problem of pollution in transportation and road traffic, especially in metropolitan areas, rise a significant concern regarding the health of the inhabitants and the rapid diagnostic procedures on site. It is important to know exactly what the problem is when it comes to toxicity in highly traffic areas. The present paper shows an applied solution for monitoring and control of pollutants, such as nitric oxides and carbon oxide in automotive and transportation sector in order to increase the potential of health security in road traffic activity. There were some measurements done in laboratory. Also the sensors were calibrated and tested. A hardware in the loop system was also used in order to test the validity of the hypotheses for monitoring and for giving the signal of hazard condition regarding pollution with nitric and carbon oxides.

The blood gas assay is one of the most important procedures that need to be performed in case of an emergency. In the intensive care, emergency, pediatrics, nephrology, neonatal it is mandatory for the results of the arterial blood gas assay to be precise and accurate. A proper mixing procedure is required before analyzing the sample in order to prevent blood coagulation and to harmonize the content. An automated mixing system can be the solution for assuring the correct analysis procedures which implies providing the correct results and the proper functionality of the blood gas analyzer. An original prototype of this kind of system will be presented in this paper.

A printed circuit board, or PCB, is a piece of hardware that acts as a base and provide electrical connections to the mounted components. PCBs are present in almost all types of electronic waste including cell phones, computers, printers, and medical devices. Waste of electrical and electronic equipment (WEEE) is one the fastest growing waste streams in the EU and is expected to grow to more than 12 million tons by 2020 [1]. The waste PCBs contain metals and major hazardous components and this make them the most difficult parts of WEEE to be recycled. Waste PCBs recycling is a preoccupation not only to their rich content, but also due to their potential risk for environment and human health. E-waste causes damage the nervous system, circulatory system, kidneys, lungs or skin [2]. The paper aims to develop a smart sorting system for components resulted from dismembered medical PCBs. The proposed application is based on image processing and it was tested at a laboratory scale. The application can be included in a complex e-waste sorting system.

The objective of this project is to realize and implement a complex system for remote monitoring of vital functions. The IOT-based health care system for the elderly is the cheapest medical device based on the IOT platform for patients and physicians. It provides a solution for measuring body parameters such as ECG, temperature, humidity and pulse. It also detects the location of patients to be sent to a doctor and in case of emergency it is possible to automatically call the emergency number accompanied by the GPS data.

Currently, the complexity of the equipment involves a problem in the training of maintenance professionals, maintenance predictive techniques being similar to medical diagnostic techniques, whenever a symptom that requires tests to diagnose the problem occurs. Total Preventive Maintenance or TPM is a type of maintenance plan used in production and various industrial fields. Overall, this is a theory about how the tools, parts and machinery used for production services are maintained so that life is as increased without incident and as safe. This concept is used to reduce maintenance costs, dead times with the aim of improving and rationalizing production and customer service. The most effective tools for preventive maintenance applications, Infrared Cameras provide the amazing ability to see what other diagnostic tools cannot. Using these cameras to discover hidden issues before they turn into serious situations, help keep your equipment in peak performance, avoiding expensive equipment damage and improving safety. Infrared thermal imaging has been used as a non-destructive and non-direct technique to examine progressive deterioration processes and failure mechanisms of different medical equipment. After the study, we can conclude that thermal imaging has major advantages over other diagnostic techniques because measuring equipment does not emit harmful radiation, thermal scanning does not require direct contact with the object to be analyzed, malfunctions are detected quickly and this procedure can be repeated whenever or needed, allowing real-time analysis.

The paper proposes a method for body or bioelectrical impedance (BI) measurement based on voltage measurement and analysis at different frequencies with a four-electrodes configuration and the principles of virtual instrumentation. The measured values are used to calculate: the effective (root mean square) values of voltages and currents, the apparent power, the active power, the phase shift, the resistance and the electrical capacity of the body. For the experiment, an NI PCI-6110 data acquisition board and the LabVIEW programming environment from National Instruments were used.

People spend a third of their life sleeping. It is essential for a good health and indispensable for the good functioning of the human body to maximize its physical and mental capacity. In the last years there was a significant increase in sleep disorders that have a big impact on people’s life quality. One of these disorders is sleep apnea, which is often not diagnosed and is common between children and adults too. Apnea is characterized by periods of breathing interruption. The most common form of sleep apnea, called obstructive sleep apnea (OSA), is caused by partial or complete obstruction of the patient’s upper airways. Normally, at each inspiration, the pressure in the upper airways decreases under atmospheric pressure, creating a tendency for collapse of the upper airways. The main aim of this paper is to design a LabVIEW based system for monitoring and detecting an episode of sleep apnea based on biomedical signals taken from different sensors.

Epilepsy is a neurological disease characterized by the presence of one or more seizures. The patient has different symptoms but the worst of them are the convulsions. This disease is marked by a variety of disorders that reflect brain dysfunction having different causes [1, 2]. In young children, epilepsy is often attributed to birth trauma, congenital abnormalities or genetic disorders and in adults to cerebral vascular accidents, tumors and cerebrovascular diseases. Epilepsy imposes on individuals and their families a tremendous physical, psychological and social effort. Early detection of this disorder is very helpful. The aim of this application was to design a low cost-system for monitoring an epileptic episode based on measured bio-parameters like temperature and wrist motion. The proposed system is implemented using a bracelet equipped with sensors connected to an Arduino board that transmits the signals to a smartphone where an Android application runs.

Employing various wireless technologies in everyday activities has increased the quality of life, exposing us to an increasing amount of electromagnetic radiation. In urban areas the electromagnetic pollution is more significant for the common mobile communication frequency bands because of the multitude of base stations deployed to serve a large amount of users. As such, when deploying new telecommunication sites, the operators must comply with the regulations and be aware of the existing EM background. This paper presents an overview of health risks for these frequency bands and focuses on the evaluation of the electromagnetic radiation while performing a measurement campaign in the central area of Cluj-Napoca for the 700–1000 MHz frequency range.

The paper proposes a solution for monitoring of cardiovascular parameters during rehabilitation after stroke. Stroke is the most important cause of long-term disability in Europe. The effects of stroke can vanish after a short period or can remain for the rest of the life depending on therapeutic program. The system developed for this study is not only therapeutically devices that use virtual reality for rehabilitation exercises but also record one or more biomedical parameters such as: electromyogram (EMG), electrocardiogram (ECG), pulse wave, heart rate (HR), respiration rate or oxygen concentration in the blood (SpO2). These physiological parameters are selected according to the physician’s prescription and the patient needs. It was observed the cardiovascular system status, analyzing the heart rate variability. During therapeutic procedure it was recorded ECG (1 lead) and heart rate variability (HRV) was calculated. The results were used to determine the stress level induced by the rehabilitation program.

The article provides to the reader a brief of the piezoelectric materials characteristics and their possibilities in biomedical microdevices development. The first section of this article presents the basics of piezoelectric MEMS. The research is focused on microgrippers since this technology is widely used in biomedical applications. The second section of this article present a review of both the direct and inverse piezoelectric effects and the piezoelectric coupling formulation used for modelling biomedical microgrippers. An analysis of piezoelectric gripper based on finite-element calculations is presented in which the fundamental electroelastic equations governing piezoelectric media are solved numerically. A study on how different geometries, different piezoelectric materials and even different mesh densities influences the performances of the microgripper are described in the last section of this article. The experimental results confirm their efficiency and demonstrate that the piezoelectric microgrippers are well suited in biomedical applications.

The seed germination test of Lepidium sativum L. offers intrinsic data obtained within this complex process and details on the mechanisms of action of two pharmacologically distinct substances, ethyl urethane, a general anesthetic and cycloheximide, an inhibitor of protein biosynthesis in eukaryotes. The rate of germination of the species gives the test efficiency and the possibility of multiple experimental versions at identical time periods. Testing was carried out in aqueous media consisting of filter paper soaked with water or aqueous solutions of the two substances. It was evaluated the frequency of seed germination and the length of the radicle at 24 and 48 h after exposure. Comparison of results was made by nonparametric and parametric statistical tests to reject the null hypothesis at p < 0.05. Germination in the control group was over 90% and the length of rootlets was over 8 mm at 48 h. Ethyl urethane 1% delayed the germination, but it reached in 48 h at values close to those of the control group. The length of the radicle was significantly reduced, less than 3 mm. At this concentration, ethyl urethane clearly, but reversibly, inhibits germination. The germination is almost blocked at concentrations of 10% ethyl urethane, the effect being irreversible and the length of rootlets is at the limit of measurement. Cycloheximide 0.01% reduces to a greater extent than ethyl urethane 1% the germination frequency and length of rootlets; the action is irreversible. Inhibitory effects on germination of ethyl urethane and cycloheximide, substances with different pharmacological targets, show the importance of the general processes of cell excitability and the participation of specific proteins in the cascade phenomenon of germination in plants.

In this paper, an example of numerical simulation of the temperature propagation in five biological media is presented. For the five spaces, successively disposed, respectively: tissue (A), tooth (B), steel (C), tooth (D) and again tissue (E), the structure parameters, respectively the time constants (T1; T2) and the space constants (S1; S2) are obtained using the dedicated program CTISP01(02) which implements equations which are presented in the paper. It is of great interest the temperature propagation in time and space, both in the interior of these spaces and at the separation limits between them. The dedicated program ZPROP03(04), that assures much flexibility and a large diversification for the similar studied applications was elaborated on the purpose of simulating the mathematical model of the propagation process, proposed in the paper. Direct applications of the presented simulations can be used in dental treatment domain.

Identification of animal species based on their sounds has already proven to be useful in biodiversity assessment. In this paper we explore the use of a combined Teager—cepstral—TESPAR (Time Encoded Signal Processing And Recognition) analysis to discriminate between different animal species. Our experiments using this approach together with classification techniques shows that TESPAR S-matrices of Teager cepstral coefficients along with some additional features can be successfully used to discriminate between different animal species, even in the conditions of small training sets.

Interest in using portable devices in neuroscience applications for people with serious motoric deficits has been growing in the last few years. The Emotiv EPOC+ headset is one such device. This study aimed to assess the ability of this headset to determine event-related potentials and especially P3. Four healthy subjects participated in this experiment during which the headset recorded potential evoked by auditory and visual stimuli. The method, the program of stimuli, the results of the measurements as well as the statistical approaches have already been established in previous studies. The measurements were performed with the headset and the software TestBench attached to the device. Data analysis was performed offline on electrodes FC5, FC6, F3, F4, P7, P8, O1 and O2. The Emotiv EPOC+ headset was capable to distinguish the characteristic deflections of the P3 component of event-related potentials. Even across a small number of subjects and trials the high signal-to-noise ratio of the device did not preclude a statistically significant result. The result obtained can be considered as a first step in determining P3 or other ERP components using Emotiv EPOC+.

Screening and diagnosis in ubiquitous healthcare environments is performed by the medical staff in the presence of a variety of medical data originating from continuous in vivo patient monitoring. This assumes the correlation of data, such as vital signs, biopotentials, activity tracking, bio-markers, etc., in the context of hybrid clinical monitoring. The hybrid patient monitoring setup envisioned in this work targets the simultaneous assessment of body fluids via electro-optical means and of electrophysiological data, i.e. electrocardiogram, via biopotential monitoring. Accordingly, the aim of this paper is to propose an electrocardiogram morphological analysis algorithm applicable in the framework of the envisioned hybrid monitoring setup. Electrocardiogram morphological analysis is performed in time domain in two stages. The R, S and Q waves are first identified via comparison to a threshold value. Then, the P and T waves are identified via cross-correlation to a reference signal. The novelty of this work is that cross-correlation is performed after the QRS complex was eliminated from the electrocardiogram. Expectedly, this leads to improved results in wave identification and to a reduction of false detections. Matlab simulation results validate the proposed procedure.

Empirical Mode Decomposition (EMD) is an acknowledged procedure which has been widely used for non-stationary and nonlinear signal processing. The main idea of the EMD method is to decompose the processed signal into components without using any basis functions. This is a data driven representation and provides intrinsic mode functions (IMFs) as components. These are obtained through a so-called sifting process. This study presents an EMD decomposition-based filtering procedure applied to ECG signals (from specific databases), the results are evaluated through signal to noise ratio (SNR) and mean square error (MSE). The obtained results are compared with discrete wavelet transform based filtering results.

Emotion recognition from speech signal has become more and more important in advanced human-machine applications. The detailed description of emotions and their detection play an important role in the psychiatric studies but also in other fields of medicine such as anamnesis, clinical studies or lie detection. In this paper some experiments using multilingual emotional databases are presented. For the features extracted from the speech material, the LPC (Linear predictive coding), LPCC (Linear Predictive Cepstral Coefficients) and MFCC (Mel Frequency Cepstral Coefficients) coefficients are employed. The Weka tool was used for the classification task, selecting the k-NN (k-nearest neighbors) and SVM (Support Vector Machine) classifiers. The results for the selected features vectors show that the emotion recognition rate is satisfactory when multilingual speech material is used for training and testing. When the training is made using emotional materials for a language and testing with materials in other language the results are poor. Therefore, this shows that the features extracted from speech display a closed dependency with the spoken language.

We propose a new algorithm for automated collagen segmentation from Masson’s trichrome stained images with two steps: color transfer from a known, optimum-stained image, followed by k-means clustering. The algorithm’s output is scored by two proficient pathologists. Results show a good segmentation output (~60%) and strong agreement on pathologist’s opinion on a good segmentation (Cohen’s kappa = 0.8063).

Hepatocellular carcinoma (HCC) represents the most frequent form of liver cancer. It evolves from cirrhosis, as the result of a restructuring phase at the end of which dysplastic nodules appear. HCC is the main cause of death in people affected by cirrhosis. The most reliable method for HCC diagnosis, the golden standard, is the needle biopsy, but this is an invasive technique, dangerous for the human body. We develop computerized methods, based on ultrasound images, in order to perform automatic diagnosis of HCC in a noninvasive manner. In our previous research, we elaborated the textural model of HCC, based on classical and advanced texture analysis methods, in combination with traditional classification techniques, which led to a satisfying accuracy. We aim to improve this performance in our current and further research. In this article, we analyzed the role of specific deep learning techniques concerning the automatic recognition of HCC from ultrasound images. We chose the Convolutional Neural Networks (CNN), this method being well known for its performance in the field of image recognition. Thus, CNN are based on artificial neural networks, they also performing image processing operations, such as inner convolutions. In order to evaluate the newly adopted technique, we assessed the classification accuracy achieved in the cases of distinguishing HCC from the cirrhotic parenchyma on which it had evolved, respectively when differentiating HCC from the hemangioma benign liver tumor. We compared the accuracy of CNN with our previous results, based on texture analysis methods and it resulted that CNN yielded better recognition rates than the classical texture analysis techniques, respectively comparable with those provided by the advanced texture analysis methods. However, further improvements will be necessary, which we mention within the last section of this article.

Researching in new technologies for diagnosis, planning and medical treatment have allowed the development of computer tools that provide new ways of representing data obtained from patient’s medical images such as computed tomography (CT) and magnetic resonance imaging (MRI). In this sense, augmented reality (AR) technologies provide a new form of data representation by combining the common analysis using images and the ability to superimpose virtual 3D representations of the organs of the human body in the real environment. In this paper we describe the development of a generic computer platform based on augmented reality technology for surgical preoperative planning. In particular, the surgeon can navigate in the 3D models of the patient’s organs in order to have the possibility to perfectly understand the anatomy and plan in the best way the surgical procedure. In addition, a touchless interaction with the virtual organs is available thanks to the use of an armband provided of electromyographic muscle sensors. To validate the system, we focused in two cases of study: navigation through aorta artery for mitral valve repair surgery and navigation through vascular structures in the brain for the treatment of cerebral aneurysms.

The healthcare industry generates a large amount of data by keeping patients’ medical history and due to the diversity of clinical medical equipment. In this paper we address problems that exist in the organ transplantation medical field. Some matching algorithms (based on centralized data) were already presented but expanding the system when it comes to Big Data was not considered before. Problems that may occur in the context of Hadoop are related to uneven data distribution and MapReduce processing. The question that arise is whether a centralized graph algorithm can be adapted to MapReduce in order that the results to be equivalent to centralized processing and efficiency to grow through parallel processing. Our solution uses intelligent agents to collect and process medical data. In case of the matching algorithm, the distributed version can approximate a solution obtained by using the centralized application, but it is more effective as a response time in the Big Data context.

One of the most commonly reported malignancy with serious health hazards in the world is oral cancer. In developing countries, the estimated cases of oral cancer are much higher when compared to the developed countries. The easiest way to detect and classify the oral cancer is by means of visual inspection and it is followed by the biopsy procedure. The inspection of oral cancer in a visual manner is not always reliable and it is based mainly on the analysis of clinical features and sometimes during its initial stage it may go unnoticed by highly trained specialists too. Therefore, there is an absolute necessity to screen and classify the oral cancer that should be quite accurate, reliable and with less human manual intervention. Here, in this paper, classification of oral cancer is given prior importance and so Probably Approximate Correct (PAC) Bayesian Classifier is used a first level classifier and then it is further optimized with the Finite Mixture Model (FMM) which is used as a second level classifier. Results show that when PAC Bayesian is used, an average classification accuracy of 96.23% is obtained for all the stages and when it is further optimized with FMM, it gives a classification accuracy of 100%.

The main objective of this paper is to introduce a public system architecture and application for emergency situations that could improve the medical services by efficiently distributing resources between a FANET (Flying Ad Hoc Network) and MANET (Mobile Ad Hoc Network) hybrid network and nearby hospitals. The proposed solution has a Fog edge node that collects medical care data from the mobile network and forwards it to the medical centers. Data transmission efficiency in a high mobility scenario is ensured by the multiple paths provided by MP-OLSR routing protocol. Furthermore, MP-OLSR is evaluated in comparison to OLSR.

Dementia is a very complex disease that affects the ability to think and remember. The thinking ability affects the daily living activities (DLAs) pattern of the people with dementia (PwD) and thus the caregivers and the healthcare professionals that are responsible for assisting PwD can take preventive actions when anomalies in DLAs are identified to improve the health condition of PwD. The main contributions of the article are: (1) the development of an approach for the anomalies detection (AD) in the DLAs of the PwD, (2) the description of the preprocessing of the DLAs data, (3) the presentation of an approach for the detection of the baseline of PwD using Random Forest (RF), (4) the presentation of an approach based on a Sequential Model (SM) for the detection of the baseline of PwD and (5) the AD in DLAs of PwD using the predicted baseline and the data monitored in a day.

In Natural Language Processing, Named Entity Recognition aims to delimit and appropriately label the chunks of text containing a specific information. The paper presents the preliminary results we obtained by using a Conditional Random Fields approach for extracting information of interest from drug prescriptions. So far, our model was trained to extract the amount of medicine, measuring unit, frequency of administration, treatment duration and the treatment beneficiary condition. The model was trained using a corpus of drug prescriptions constructed and annotated by hand. The results obtained so far indicate the CRF model we developed performs well, scoring a 91% F1 score on the test set.

Accurate body temperature measurement is imperative in pediatric assessment and can signal symptoms such as fever onset. This paper presents the development of a Bluetooth enabled pediatric temperature monitoring device, envisaged for home usage. The temperature monitoring device consist of a skin temperature sensor, OLED display, PIC microcontroller, Bluetooth module and a power supply unit. The measured temperature data are wirelessly transmitted via Bluetooth protocol to a PC. Data storage and visualization is provided by a LabView interface. The results are presented and discussed.

The paper presents some considerations on the development of an external system of sensors for post-stroke robotic assisted rehabilitation. A conceptual integrated system which places the patient as an active component is proposed. A set of bio-signals and the corresponding sensors are described to use the data as real-time information during rehabilitation exercises. A novel robotic system is presented for bed confined patients with its kinematic structure and workspace generation for medically relevant motions along with the positioning of the system of external sensors.

This paper present an experimental study that evaluates the performance of a Motor-Imagery (MI) Brain-Computer Interface (BCI) using different electrodes configuration in order to determine the most efficient usage of an 8-channels limited biosignal acquisition device. It is well known the fact that biosignal acquisition devices tend to be very expensive, especially if they have more than 8 electrodes: if in a research context this cost is manageable, for care giving institutions this cost is often prohibitive, which drastically limits the research transfer to practical applications Therefore, it is important to determine the most efficient way in which a more affordable device might be used. A total of 19 configuration were tested, and the results compared against each other. Recommendation for further testing are made.

Heat generation in angular contact bearings, dynamic analysis and optimization of high speed spindle bearings require to know the load-displacement values in for bearing components. The equations that describe the relationship among preload, speed, and contact angle are solved usually using iterative methods. A new method that uses genetic algorithms is proposed to solve the algebraic system with multiple dependencies with a good precision in evaluation of angular contact angle.

This paper presents aspects of modeling an original complex assistive system designed to work in two ways; first, ensuring mobility and second, assisting and regaining the ability to walk.

Almost 15% of the planet’s population (approximately 785 million people) suffer from mental or physical disabilities, with 5% of children in this segment, according to a report issued by the World Health Organization. In the whole world, the estimated number of wheelchair users is over 130 million people. It is estimated that only 5–15% of people in need of wheelchairs own and hold one. In countries with a life expectancy of over 70 years, people spend an average of about 8 years or 11.5% of their life, living with a disability [1]. To help people with movement disabilities who suffer from Tetraplegia (complete loss of lower and upper limb movements), we have made a voice-driven mobile platform for movement. The voice recognition system was adapted to a wheelchair and programmed to perform basic movements for patient movement. At the wheelchair used by us has been attached a sensor system to avoid impact with certain objects. For Voice Recognition we used the EasyVR voice recognition module and an Arduino Mega 2560 module. The power side for controlling the two engines was made with IGBT transistors.

After hip arthroplasty can occur morphological, functional and psychological complications, as a result of a complex of determinants. Preserving a good quality of life must be our first aim. Rehabilitation is one of the major key in preventing and treating. From a health perspective, the existence of one or more limitations due to physical or mental impairment, has a major impact over the quality of life is strictly related and reduced well-being during illness.

Cancer is considered as the disease of the XXI century being still one of the deadliest afflictions even though continuous advancement is achieved in the treatment of different malignances. In parallel with the technological progress minimally invasive therapies like radiofrequency, ablation, and targeted drug delivery attempted to provide methods that minimize the side effects while maximizing the therapeutic impact. Taking into consideration the number of elderly people that is expected to increase over the years to come, cancer therapies must progress to ensure a real improvement of the quality of life. This paper is an overview of the evolution and challenges of robotic systems for minimally invasive procedures (MIP) that covers both surgical and non-surgical therapies for cancer diagnosis and treatment. A benefit of using robotic assisted MIP in cancer treatment is the high precision/low adjacent damage to neighboring tissues which supervised by different real-time monitoring solutions represent the cornerstone in the future advancement of cancer treatment technologies.

Diabetes is a chronic illness in which disease management is crucial in preventing associated complications. Patient satisfaction with medical care is closely linked to patients’ treatment adherence and disease management. In the context of an increased number of patients diagnosed with diabetes each year, the research we propose analyses the influence of socio-demographic, psychological and medical variables on patient satisfaction with diabetes care in the hospital setting in Romania. The research was conducted using mailed patient satisfaction questionnaires between July 2014 and February 2015 on 339 diabetes patients in Romania. The response rate was 39.5%. Results show that the most important factors influencing patient satisfaction with diabetes care in the hospital setting are patients’ age, educational and income levels, diabetes type, whether or not the patient incurs associated complications and patients’ perspective on diabetes management.

Patient satisfaction is an important indicator of medical care. Existing literature suggests patient satisfaction has a considerable influence on patient retention rates, medical outcomes, treatment adherence, as well as on medical staff satisfaction or patients’ intent to seek a second opinion. Furthermore, the past couple of decades have also brought significant changes to the medical systems and practice around European countries. Such changes include the development of private medical care units, increased competition in the medical sector, the availability of considerable medical information on the internet, as well as a strong tendency to have patients positioned as partners in the patient-doctor relationships. As a consequence, patients today demand time and answers to their questions, as well as empathy, politeness and attention from their physician. Although all these changes strongly affect the medical surrounding, the literature investigating patient satisfaction from a marketing perspective remains scarce. The article takes on this challenge and aims to investigate patients’ expectations and satisfaction regarding the services offered to them by their family physician (GP). A qualitative exploratory study was conducted in the form of three focus groups with undergraduate students in Romania. Results showed that attention given to patients plays an important role in satisfaction together with reduced waiting times. The added value of the article lies in its investigation regarding patients’ expectations form their family physician which can represent a starting point for the latter in adapting and improving their services. Furthermore, the article brings new information regarding patients’ expectations in terms of their physician’s online presence, which can help the latter develop new services for their patients. The article is particularly addressed to family physicians and professionals in the medical and marketing fields involved in drafting policy, medical services or marketing strategies for family physicians practices.

Introduction: CT scanning generate tridimensional reconstructions to permit the observation of paranasal sinuses and nasal cavity, and other anatomic structures of our body. The use and application of the 3D reconstructions generated from files of CT examination. The evaluation before sinus surgery through 3D reconstructions from the CT files may help the surgeon for diagnosis, preoperative planning and to acquire more information than with the traditional two-dimensional images obtained with the three different plans: axial, coronal and sagittal. Objective: To investigate and demonstrate the reliability and the feasibility of the evaluation before sinus surgery through 3D reconstructions from CT examinations of patients with a free software. Method: The reconstructions were carried out before the surgeries in order to assess the paranasal sinuses and nasal cavity for 45 patients. After this study, the surgery was digitally stored. Conclusion: With simple tools and personal computer, we evaluated the possibility to generate 3D reconstructions, the preoperative knowledge of the paranasal sinuses and nasal cavity may generate benefits during the performance of surgeries.

The provision of today’s health services depends on a steady increase in the evolution of medical technology. There is no hospital department that has not felt the impact of electronic, mechanical, hydraulic equipment in daily routine. The development of medical technology, the complexity of medical equipment has been rapid, producing a proliferation of growing medical devices. This paper was conducted to provide a comprehensive study evaluating the maintenance and repair program for medical equipment to determine the optimal method for a cost-effective management system and to identify risk factors. When a risk assessment tool is being developed, quantified and implemented, many applications are possible to generate procedure risk monitoring presentations across the institution to implement a technical competence program for biomedical/clinical engineers, technicians and clinicians.

The aim of the study was to assess and analyse the oncologic postoperative outcome of patients after robotic surgery for rectal cancer We conducted a study on patients with rectal cancer undergoing robotic surgery at the 5th Surgery Clinic of the Municipal Clinical Hospital in Cluj-Napoca between January 2010 and December 2013 and evaluated postoperative survival after 5 year follow-up. There were 10 patients, median age was 62 ± 11 years. Five anterior rectal resections, three lower rectal resections and two abdominoperineal resections were performed. Most tumors were stage III (6 cases). Of the patients included in the study, 7 patients survived and 3 patients died during the 5-year follow-up period. Survival at 5 years after robotic surgery was similar to open or laparoscopic surgery. Robotic surgery may be an alternative to laparoscopic surgery in the treatment of rectal cancer, especially with regard to the identification and preservation of nerve plexuses and dissection in a narrow pelvis with similar oncologic outcome.

The aim of the study was to identify lymph node micrometastases in order to demonstrate the prognosis of colorectal cancer patients staged I and II undergoing curative surgery. We conducted a prospective study on a total of 44 patients with stage I–III colorectal cancer, undergoing radical surgery at the Fifth Department of Surgery of Cluj-Napoca Municipal Clinical Hospital between September 2012 and January 2015. For the identification of micrometastases we used the sentinel lymph node mapping by two techniques, in vivo and ex vivo. In N0 patients we conducted an immunohistochemical study to identify micrometastases. Patients were followed 3 years after surgery to identify possible relapses. The mean age was 63 years, 24 patients were males and 20 (45.5%) women. Ten patients (12.8%) had stage I cancer, 12 patients (27.3%) had stage II cancer, and 22 had stage III cancer. Sentinel lymph node detection rate was similar for the in vivo technique and for the ex vivo technique. The percentage for the detection of micrometastases was 25% in vivo and 33.3% ex vivo. The 3-year postoperative recurrence rate was 25% in overstaged patients. The presence of micrometastases should be considered as a negative prognostic factor in patients with stage I and II colorectal cancer.

Introduction. Nanomedicine is the medical application of nanotechnology and concerns the use of precisely engineered materials at nano length scale, to early detection and prevention, improved diagnosis, proper treatment and follow-up of diseases. This new and exciting specialty finds more and more applications in all medical fields, the otology being part of them. This review considers current developments and future prospects for metallic nanomaterials used in otology. Materials and Methods. The online medical reference databases PubMed, Google Scholar, ISI Web of Science and Science Direct were searched with search terms “Nanotechnology, Nanomedicine, Metallic Nanoparticles” in combination with “Otology, ENT, middle ear, inner ear diseases” in turn. Furthermore, we are giving an overview of the work of the Department of Otorhinolaryngology, Head and Neck Surgery, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca and Tumor Biology Department, The Institute of Oncology “Prof. Dr. I. Chiricuta”, Cluj-Napoca Results. Metallic Nanoparticles proved to have strong anti-bacterial, anti-viral, and anti-fungal activities by the inhibition of biofilm formation, destruction of viruses and fungi and stimulation of the host’s immune response. These properties make metallic nanoparticles such as silver nanoparticles extremely attractive to be used to treat middle ear infectious diseases such as otitis media. For the inner ear diseases many studies have used metallic nanoparticles to deliver drugs, genes, and growth factors. The current limitations for the clinical application are related to their possible cytotoxic effect. Conclusions. The future treatment of otological diseases could be revolutionized by advances in nanomedicine. The current review suggest that further studies are required to be able to confirm the safety of metallic nanoparticle derived application to use in life.

The development of patients’ electronic healthcare records has been hampered by bureaucracy and by heavy regulation within the medical field. Medical data recorded in a patient health records is a valuable source of information that can be used by doctors and researchers to improve the quality of healthcare and the quality of life. Medical data should be owned and controlled by the patient instead of being scattered in different healthcare systems that does not support transfer and semantic interoperability between different healthcare providers. Blockchain technology has demonstrated in the financial field that it is possible to create a safe, secure and auditable mechanism by using a decentralized network along with a public ledger. But with the adoption of the newly General Data Protection Regulation, all technological advances discovered by the Blockchain are now blocked. In this paper we present the main aspect of the GDPR and Blockchain technology in healthcare and a way in which this two can work together.

The dental enamel is the hardest surface of teeth. Depending on the mechanical and tribological properties of the enamel, the sustainability of the teeth can be appreciated. These properties are influenced by the mastication conditions including humidity, temperature and abrasion effects. The aim of this work it is to consider the effect of temperature on tribological and mechanical properties of restorative dental materials using advance techniques. Nanoindentation provides information about hardness and elastic modulus. The tribological investigation in this paper is summed up to measure the friction force as a function of temperature. A temperature control system is used to monitor the temperature of investigated samples in the range of 10–60 °C. For this purpose an atomic force microscope with a nanoindentation module was used for the experimental determination of the mechanical and tribological properties of the dental materials taking into account the temperature variation. These relatively non-destructive mechanical characterization techniques can help to better understand the mechanical behavior of dental materials and thus facilitate their preparation with excellent mechanical and tribological properties.

Magnetic submicron systems based on N-palmitoyl chitosan, magnetite and chemotherapeutic agent (Paclitaxel) have been prepared via ionic gelation mechanism combined with ultrasonication technique. Dynamic light scattering results showed that magnetic particles size, measured in aqueous medium is around 300 nm and the structures have positive surface charge given by the non-substituted amino groups of chitosan. In vitro release studies have shown the ability of magnetic particles to release the chemotherapeutic drug in a controlled manner over 24 h. It has been observed a more pronounced drug release within slightly acidic media (pH = 6.8) as a result of the higher polymer swelling and degradation.

The paper aims at presenting some simple and effective tools that can be used by medical engineering students in steering their research in relevant directions. This way, the results of their graduation projects may serve to address some real and urgent issues in their field of expertise. In order to achieve this goal, the students need simple and effective tools that provide reliable and fast results without involving additional skills. Therefore, the paper will present two situations of Medical Engineering and Optometry students in search for the suitable research topic for their graduation project, so that it responds to practical needs occurred from the social environment.

Waste of electronic medical devices contains different type of valuable plastics intermixed, generating incompatibilities and limiting the reusing potential, so that the separation of plastics is a crucial operation in recycling. The tribo-electrostatic separation, based on charging the plastic mixture in a tribocharging device then separation of charged granules in high intensity electric field is an efficient method. The paper analyses the influence of sample weight, fluidizing air flow rate, and the shape of the tribocharging chamber on the efficiency of a fluidized-bed tribocharging device with the aim to improve the plastic mixtures separation. The results highlight that the granules charging in fluidized bed has greater efficiency if the section area of the tribocharging chamber is constant, with constant fluidizing air speed. The granules charge in fluidized bed devices increases with the number of collisions but in a greater measure with the impact energy between granules.

Additionally to residual ozone, in processed aqueous solutions using intense electric fields, free radicals are present and determines changes of a variety of physical parameters—chemical of solutions. Ozone and free radicals remaining in the aqueous treatment processes are primarily responsible for harmful inhibiting, but also are useful for biostimulation processes of living environments (increasing the speed action of polymorphonuclear leukocytes in the healing of severe infections, changes of the pattern of collagen regeneration during ulcerations healing). This paper presents the results of a multidisciplinary research, with extensive scientific and technical aspects. Intense electric fields, especially using corona point or filiform discharge electrodes, used in specially designed treatment cells and the processes of air ionization, generates and trains a variety of electrical charge carriers, which have sufficient energy in order to brake different gas molecules, in order to produce oxygen, or to determine the generation of ozone and free radicals in retention solutions or in the present environment. The electric field parameters, the intensity, the nature and shape of high voltage, exposure time, but also the characteristics and structure of cell treatment (multipoint, filiform or brush type electrodes), gap size or the step between the discharge electrodes, all are important parameters which determines the presence and concentration of ozone and free radicals which, present in the processed aqueous solutions.