Wireless Mobile Communication and Healthcare

Usability tests play an important role in any kind of software, as they limit errors and misunderstandings. Especially in the growing market of medical applications it is indispensable, but time-consuming and expensive. In order to improve the quality of medical applications and remove obstacles for developers, a method has been developed that simplifies testing the usability of mobile medical applications and provides additional data on compliance and effectiveness. Because this test method is remote-controlled and asynchronous, finding examiners is simplified. It also allows more subjects to be found and more data to be collected. This increases user experience and achieves more natural results as study participants act in their natural environment. In order to decide whether the app developed is suitable for this remote testing method, a questionnaire was developed to assist in the decision-making process. The described method will be tested in a study.

Celiac disease affects an estimated 1% of the population. The only existing treatment is a strict gluten-free diet but there are myriad aspects of managing the disease that affect the lifestyle of both the CD patient and those close to them. The goal of this study was to design, develop and test a prototype of a mobile application to promote wellness and support for individuals with CD. The proposed application’s aim is to serve as a platform for CD patients and members from their social circle, to help with sharing general and specific information about four lifestyle aspects: social, emotional, food, and wellness. The application aids with the management of a gluten-free diet from the social circle perspective for the specific CD patient. Perceptions towards the usability of the application were gathered from 22 participants and analyzed via a USE questionnaire. The results from the survey reported overall satisfaction of the prototype and useful insights were gathered for subsequent versions. The general expected benefit of this evidence-based application is improved quality of life for the CD patient due to their social circle being well informed about the management of the disease and its potential complications.

Objective: Cerebral edema, as a common secondary disease after stroke, can result in brain hernia and even death, effectively monitoring the process of cerebral edema do benefit the prognosis of stroke patients. While current methods have their inherent drawbacks, we utilized a novel frequency shift (FS) method to reflect the severity of cerebral edema. Method: In this paper, 12 rabbits (10 rabbits for experimental group and 2 rabbits for control group) were enrolled in the 24 h monitoring experiment. Those rabbits underwent monitoring utilizing a novel flexible conformal coil sensor, for which the FS induced by changed equivalent impedance of brain was extracted as the evaluation index. Findings: The results showed that this novel coil sensor can effectively monitor the process of cerebral edema. This innovative method has great potential in clinical usage which can assist medical staff conducting timely treatment in terms of its early warning capability.

This study examined the perception of end-users regarding the monitoring process offered by an innovative cardiac self-care system. The main goal was to assess the efficacy of the process implemented by a smart device designed to support people for real-time monitoring of cardio-vascular parameters in everyday life, thereby encouraging patients to be more proactive in heath management. Most participants showed positive response about the potential benefits of the proposed self-care solution and were willing to adopt the system despite some concerns related to trust and privacy.

Walking has been attracting attention as an important means for prevention and improvement of lifestyle diseases, such as high blood pressure and diabetes. However, walking at a continuous pace with high load can be challenging, and health benefits cannot be expected when walking with low load. A walking pace support system is necessary in order to achieve effective walking. Hence, we are developing BeatSync, a smartphone application that realizes the induction of a natural and accurate walking pace by the rhythm of music. This application can select songs from a user’s music library. However, some songs, such as songs with a fast (slow) rhythm or complex beats, are not suitable for walking pace induction. In the present paper, we consider the speed and clarity of music rhythm to be an important factor in selecting a song that is suitable for walking pace induction and make an index and clarify its effect on walking pace induction. In the present study, BPM is used as an index of rhythm speed, and RhythmValue (RV) is proposed as an index of rhythm clarity. In order to verify the effectiveness of the index, we conducted walking pace induction experiments using 30 songs with different speeds and clarities (two sets of 15 songs) with 14 participants. As a result, the experiments confirmed that the proposed index can distinguish songs that are suitable or unsuitable for walking pace induction and can select songs that are suitable for walking pace induction.

Nowadays the design of interfaces on mobile devices in the field of mental health is being studied to be applied in the functional criteria related to usability and user experience (UX). This article presents a methodological and conceptual development of an innovative telematics application oriented to control and management relapse prevention in bipolar disorder patients created by the Psychiatry and Clinical Psychology Unit of La Fe Hospital and the Polytechnic University of Valencia. Application called e-therapy aims to control affective diseases in bipolar disorder through the use of computer-assisted tests related to depression and mania among others. Its development and design took into account aspects of functionality and visual usability aimed at people with affective diseases related to mental health. Therapists, psychologists and doctors can monitor and verify patient’s mood in real time as well as detect changes in their vital and affective trajectory that allows early intervention and relapse prevention.

Everyday life is driven by a wide range of mental processes organized in cognitive, emotional and executive functions. The assessment of these abilities could be improved thanks to the rising of Virtual Reality (VR) technologies, that show a more ecological validity in respect to the artificial laboratory settings. Moreover, mental processes can be investigated via electrophysiological measures, due to the modulation of deep structures controlling the autonomic system, and in turn peripheral organs activity. According to scientific literature, measurements could derive from sensors over periocular area, that is the same area covered by a typical VR headset.

The aim of this paper is to introduce the PERFORM prototype, a wearable mask with embedded sensors able to collect biomedical signals in a non-obtrusive way for the assessment of online cognitive abilities in VR scenarios. We show that PERFORM can collect data related to cardiac pulse, galvanic skin response, movements and face temperature during cognitive tasks in VR. Thanks to the specific electrode placement and the employment of VR scenario, PERFORM will be an ecological tool to assess psychophysiological correlates of online cognitive performances.

Healthcare delivery in rural America poses additional challenges than its urban counterpart. Rural locations more commonly face shortage of physicians, a lack of high-paying jobs with adequate insurance benefits, transportation, health literacy, a stigma with health conditions due to lack of anonymity and difficulties accessing specialty care. Rural communities see higher rates of suicide, heart diseases, respiratory disease, stroke, social isolation, and public health crisis such as the opioid epidemic. More than 46 million Americans, or 15% of the population, live in rural areas within the United States.

Communities play an important role in the health of their residents, as social and economic factors, physical environment, and healthy behaviors make up 80% of an individual’s overall health, while clinical care accounts for only 20%. Chronic disease doesn’t occur in isolation. Conditions such as diabetes, asthma, heart disease, and obesity are all tied very closely to the environments, culture, and behaviors that surround individuals. Therefore, a significant amount of human health is determined beyond clinical care. For many individuals who are at an elevated risk of developing chronic disease, episodic care that begins and ends inside a hospital or clinic is not adequate to accurately treat the patient.

We propose a holistic mHealth community model for residents to overcome significant barriers of care in rural America by providing an application capable of integrating multiple health and safety data sources through a mobile digital personal health library application. Users are able to securely share their health data with others (e.g. primary care physician, caregiver). Artificial Intelligence (AI) algorithms can strategically connect residents to community resources and provide customized health education aimed at increasing the health literacy, empowerment, and self-management of the user. Communities can use de-identified population health data from this model to improve decision-making and allocation of community resources.

Anxiety-related disorders have a strong impact on our quality of life. With their epidemiological prevalence, across the population, highly exceeding the capacity for treatment in health facilities, new ways of delivering therapies are needed. The wide availability of mobile technologies, e.g., smartphones, has provided an accessible and ubiquitous platform for delivering psychological therapies and many mobile health (mHealth) systems have been proposed to support users in managing their levels of anxiety. However, many of the available tools provide features without evidence-based support of their adequateness and effectiveness. Furthermore, several tools are designed without specifically considering the users’ needs and motivations, resulting in poor adherence or a lack of motivation for systematic use, hindering any positive effects.

Considering the need to more closely focus on the motivations of the target users, this article describes how the efforts of a multidisciplinary team are contributing to support a user-centred approach to design and develop a tool to support anxiety management in the context of an Academic Campus. As a first materialization of this ongoing work, a proof-of-concept application is proposed (StopAnxiety), developed by adopting an iterative approach, and already providing a set of clinician-approved anxiety management techniques.

The concept of an Integrated Clinical Environment can be implemented by a fully connected operation room containing devices from different manufacturers. An exchange architecture and protocol for this kind of environment is defined by the IEEE 11073 Service-oriented Device Connectivity family of standards. Therein, a Domain Information and Service Model is bound to the Medical Devices Communication Profile for Web Services, which is the specification for the information exchange technology. It is employed as the communication layer in the software library SDCLib/J that implements an Integrated Clinical Environment. In order to demonstrate that the functionality of SDCLib/J is independent of the underlying transport technology, its communication layer was replaced with an implementation of the Data Distribution Service. Therefore, its publish-subscribe pattern needed to be redesigned and transformed so that it matches the library’s request-response principle.

Emotions play a key role in our life experiences. In interactive systems, the user’s emotional state can be relevant to provide increased levels of adaptation to the user, but can also be paramount in scenarios where such information might enable us to help users manage and express their emotions (e.g., anxiety), with a positive impact on their daily life and on how they interact with others. However, although there is a clear potential for emotionally-aware applications, they still have a long road to travel to reach the desired potential and availability. This is mostly due to the still low translational nature of the research in affective computing, and to the lack of straightforward, off-the-shelf methods for easy integration of emotion in applications without the need for developers to master the different concepts and technologies involved. In light of these challenges, we advance our previous work and propose an extended conceptual vision for supporting emotionally-aware interactive ecosystems and a fast track to ensure the desired translational nature of the research in affective computing. This vision then leads to the proposal of an improved iteration of a generic affective modality, a key resource to the accomplishment of the proposed vision, enabling off-the-shelf support for emotionally-aware applications in multimodal interactive contexts.

The individual experience of inadequate or insufficient sleep is one of the most common health issues in the industrialized world. The 65% of Italian population reports disturbed sleep experiences, while chronic sleep disorders affect about 10% of the population. The people with inadequate and unsatisfactory sleep often suffers drowsiness during the day associated with both somatic and mental disorders. For these reasons, the systematic and continuative monitoring of sleep is one of the main objectives in preventive, personalized and participatory sleep medicine. The purpose of this paper is to describe the architecture of a “smart mattress’’ (SmartBed) that is the main outcome of the Italian R&D project called LAID. SmartBed will be able to non-obtrusively collect physiological and environmental parameters and signals, to processing them and to provide information about the quality of sleep, the levels of stress, and more generally the well-being of an individual. Specifically, SmartBed will be able to estimate data relating to cardiorespiratory activity, movements, body position, snoring and environmental parameters. SmartBed aims to obtain a continuative and ecological assessment of sleep and well-being of a person, in order to improve his quality of life. SmartBed will be a fundamental tool for carrying out both longitudinal and epidemiological studies on the quality of sleep and life on general population.

Objective: Timely and effective discrimination of hemorrhagic stroke and ischemic stroke can significantly improve the prognosis. Current discrimination is expensive and has the disadvantage of having to be in contact with the patient. Based on animal experiments, in this paper, microwave measurement technique is used to study the discrimination of two stroke types. Method: In the experiments, 10 rabbits (5 cerebral hemorrhage and 5 cerebral ischemia) are selected. Cerebral hemorrhage is induced by injecting autologous blood (1 to 4 mL) into the brain of rabbits, and the cerebral ischemia is induced by bilateral common carotid artery ligation and femoral artery blood extraction. The two groups are monitored by a 16-channel microwave detection system to obtain the reflection parameter caused by pathological changes in the brain. After redundancy removed from original data, support vector machine (SVM) is used to identify the type and severity of two types of stroke. Findings: The study shows that the microwave-based stroke identification system can effectively distinguish the cerebral hemorrhage model and the cerebral ischemia model. The experimental system is very promising in pre-hospital stroke type identification because of low cost, non-invasive, simple operation and rapid measurement.

This work presents the development of an assistive system for the elderly in their home environment. The purpose of this system is to provide them support and extend their autonomy in order to extend life expectancy and improve quality of life when living at home. This work explores various technological innovations and technology building blocks, such as open software and open hardware. In this work, a low-cost and small-scale ubiquitous system was developed that does not disrupt the prevailing conditions in the elderly’s home. Also, a part of this work has been developed, keeping in mind elderly people suffering from dementia, offering a sufferer-centered solution.

This paper presents a novel two-fingers exoskeleton kinesthetic interaction in Virtual Reality (VR): the proposed design of the exoskeleton prioritizes the performance of the device in terms of low weight, good adaptability to different size of the human hand. This design made also the exoskeleton well wearable and allows strong force feedback which is an important parameter for a realistic kinesthesis of manipulated objects in VR.

This paper presents an integrated EMG-based system for controlling a 5-fingers robotic hand: the system combines two commercial products, namely an Open-Bionics Hand and a wearable MYO controller in a new fashion where the end-user can control different postural grasping through an intuitive menu, cycling among different pre-set grasping configurations. According to preliminary tests, such a solution may represent an interesting novelty for a user-centered experience of patients with an upper limb prosthetic device.

Minimally Invasive Surgery and, in particular, Robotic Minimally Invasive Surgery may benefit from the integration of Haptic device: here we propose a preliminary study on a two-finger exoskeleton for kinesthetic feedback of surgeon thumb and index finger while controlling a Da Vinci Robotic Device through its Master Tool Manipulator (MTM). Simulation of contact between rigid and soft objects with the Patient Side Manipulator (PSM) are integrated with Force Feedback on the MTM coupled with the exoskeleton.

Stress is a major health problem in this century, and it is associated with adverse health consequences. Its prevention and management are a great challenge, and only a minority of the affected persons receive treatment. New digital technologies offer opportunities to provide effective psychological interventions to address the negative consequences of occupational stress. However, the knowledge of the importance of different functions and features of digital stress management systems remains largely unexplored. This work closes that research gap by conducting a Delphi study, in which 20 experts prioritized requirements in three rounds. The purpose of the present study is to enable developers of digital stress management systems (DSMS) to profitably select and use functions and characteristics of those systems, taking into account the available resources. Thus, the aim is to find DSMS that better counteract excessive stress. Finally, 82% of all requirements meet the consensus threshold.

Sleep is a one of the most important activity for maintaining the health and well-being of each subject. In order to monitor continuously the quality of sleep of the general population in non-invasively way, we developed an innovative sensorized “smart” mattress (SmartBed). SmartBed is equipped with sensors to detect environmental and subject-related information. In particular, SmartBed is equipped with accelerometers and a sensing textile matrix able to detect the distribution of pressures of a subject laying on the mattress. The purpose of this work is to demonstrate how the sensing textile matrix is not only able to detect how the subject is positioned on the mattress over time, but also it allows to detect other physiological parameters and in particular the subject’s respiratory activity. In this work, we show that: (i) the sensing textile matrix allows a precise position detection; (ii) it is possible to extract accurately the respiratory frequency from the sensing textile matrix by using a specifically tailored algorithm. In conclusion, the sensors integrated in SmartBed make possible to detect important information (position and respiratory activity) to determine the quality of a subject’s sleep in a robust, accurate and non-invasive way.

Nowadays, wearable devices enable us to collect biological data from a massive number of people. However, the reliability of the collected data varies due to various factors such as band tightness and incorrect attachment. In this paper, we investigate the band tightness estimation by using an inertial sensor of a wrist-worn device. First, we analyze the relationship between the band tightness and the data reliability through a preliminary experiment. Then, we design the band tightness estimation as a classification problem based on frequency domain features. The evaluation results show the effectiveness of the frequency domain features, achieving the accuracy of 81.7% for the 3-class band tightness classification.

Traditional cloud-centric architectures for Internet-of-Things applications are being replaced by distributed approaches. The Edge and Fog computing paradigms crystallize the concept of moving computation towards the edge of the network, closer to where the data originates. This has important benefits in terms of energy efficiency, network load optimization and latency control. The combination of these paradigms with embedded artificial intelligence in edge devices, or Edge AI, enables further improvements. In turn, the development of blockchain technology and distributed architectures for peer-to-peer communication and trade allows for higher levels of security. This can have a significant impact on data-sensitive and mission-critical applications in the IoT. In this paper, we discuss the potential of an Edge AI capable system architecture for the Blockchain of Things. We show how this architecture can be utilized in health monitoring applications. Furthermore, by analyzing raw data directly at the edge layer, we inherently avoid the possibility of breaches of sensitive information, as raw data is never stored nor transferred outside of the local network.

Current wellness technologies are capable of monitoring wellness related parameters even 24 h a day for multiple days. The aim of the current research was to study the usability, user experience, and wellbeing impact of the wellness analysis Firstbeat, which is based on continuous measurement of heart rate variability (HRV) and user activity. 42 persons in working life participated in an intervention study, in which their wellbeing was continuously monitored for 3–7 days and they received a detailed wellness report and a personal plan for improvement. In a follow-up questionnaire, the participants reported good usability and user experience for the system, as well as significantly reduced stress and increased self-esteem, while no significant changes were observed in the other measured aspects related to subjective wellbeing. The results suggest that the usage of continuous wellness measurement systems using electrodes in the chest area, such as Firstbeat, can be experienced positively by their users. Further research is needed on effective methods for utilizing the rich information from the measurements in achieving lasting positive changes in lifestyle.

The paradigm of citizen-science, i.e., scientific research that is conducted in whole or in part by non-professional scientists, has gained popularity lately, e.g., for the purpose of crowdsourced data collection. Smartphones with their abundance and ubiquity are perfectly suited and have been widely used for crowdsourced data collection in real life settings. The ongoing, EC-funded research programme named BigO exploits the citizen-science paradigm to collect behavioral (eating, sleeping and physical activity) and affective (mood) data from children populations by means of a novel smartphone application with the intention of developing a decision support system to assist public health authorities in effective policy making against childhood obesity. This paper presents the development – in the context of BigO – of the myBigO app, one of the first citizen-scientist smartphone applications addressed to children for behavioral and affective data collection. This includes the design, implementation, and deployment of myBigO app in a number of data collection studies as well as its preliminary evaluation with respect to technical robustness and user experience in the context of these studies.

The necessity of using food data in mobile health applications is often linked with difficulties. In Europe no standardized and quality-controlled food product databases are accessible. Data from third party sources are often incomplete and have to be checked carefully before use for errors and inconsistencies. The purpose of this approach is to improve data quality and to increase information density by developing a dedicated food data warehouse. By using the extract, transform and load processes known from data warehouse technologies, multiple data sources will be combined, inserted and evaluated. The data is cleaned up by using data profiling techniques. Data mining methods are used to merge the datasets from food composition databases and food product databases to increase information density. The aim is to analyze, if and how Big Data technologies can increase performance of data processing significantly.

Automatic recognition of user’s activities by means of wearable devices is a key element of many e-health applications, ranging from rehabilitation to monitoring of elderly citizens. Activity recognition methods generally rely on the availability of annotated training sets, where the traces collected using sensors are labelled with the real activity carried out by the user. We propose a method useful to automatically identify misbehaving users, i.e. the users that introduce inaccuracies during the labeling phase. The method is semi-supervised and detects misbehaving users as anomalies with respect to accurate ones. Experimental results show that misbehaving users can be detected with more than 99% accuracy.

The paper presents a mobile app designed to be used by health care providers, mainly by the nurses that pay visits to the homes of the clients/patients of the health care providers. The app should optimize the nurses activity and also the communication between the nurses and the coordinators and between the nurses and the patients. The described mobile app is part of a larger software platform as will be described in the article.