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Machine learning algorithms have become popular in diabetes research, especially within the scope of glucose prediction from continuous glucose monitoring (CGM) data. We investigated the design choices in case-based reasoning (CBR) approach to glucose prediction from the CGM data. Design choices were made with regards to the distance function (city-block, Euclidean, cosine, Pearson’s correlation), number of observations, and adaptation of the solution (average, weighted average, linear regression) used in the model, and were evaluated using five-fold cross-validation to establish the impact of each choice to the prediction error. Our best models showed mean absolute error of 13.35 ± 3.04 mg/dL for prediction horizon PH = 30 min, and 30.23 ± 6.50 mg/dL for PH = 60 min. The experiments were performed using the data of 20 subjects recorded in free-living conditions. The problem of using small datasets to test blood glucose prediction models and assess the prediction error of the model was also addressed in this paper. We proposed for the first time the methodology for estimation of the impact of the number of subjects (i.e., dataset size) on the distribution of the prediction error of the model. The proposed methodology is based on Monte Carlo cross-validation with the systematic reduction of subjects in the dataset. The implementation of the methodology was used to gauge the change in the prediction error when the number of subjects in the dataset increases, and as such allows the projection on the prediction error in case the dataset is extended with new subjects.

The following paper presents a comparison study of various machine learning techniques in recognition of activities of daily living (ADL), with special attention being given to movements during human falling and the distinction among various types of falls. The motivation for the development of physical activity recognition algorithm includes keeping track of users’ activities in real-time, and possible diagnostics of unwanted and unexpected movements and/or events. The activities recorded and processed in this study include various types of daily activities, such as walking, running, etc., while fall activities include falling forward, falling backward, falling left and right (front fall, back fall and side fall). The algorithm was trained on two publicly available datasets containing signals from an accelerometer, a magnetometer and a gyroscope.

Wearable and Internet of Things (IoT) devices have the potential to improve lifestyle, personalize receiving treatments or introduce assisted living for elderly people. However, service delivery depends on maintaining and troubleshooting device connectivity to smartphones, where user engagement and technology proficiency represent a possible barrier that prevents a wider adoption, especially in the elderly and disabled population. Low-cost and low-power wearable and IoT devices face challenges when operating out of range of known home networks or pared devices. We propose an architecture and methods to provide seamless connectivity (Se-Co) between devices and wireless networks while maintaining low-power, low-cost and standards compatibility. Through Se-Co, the devices connect without user interaction both in home and in unknown roaming networks while maintaining anonymity, privacy and security. Roaming networks approve data limited connectivity to unknown devices that are able to provide a valid anonymized certificate of compliance and no harm through a home provider. Se-Co enables shifting data processing, such as pattern processing using artificial intelligence, from a wearable device or smartphone towards the cloud. The proposed Se-Co architecture could provide solutions to increase usability of wearable devices and improve their wider adoption, while keeping low the costs of devices, development and services.

The diffusion of medical devices is expanding at an astonishing rate. The increasing number of novel patents per year suggests this growth will continue. In contrast to drugs, medical devices are intrinsically dependent on the environment in which they are used and how they are maintained. This created an unprecedented global need for well-trained biomedical engineers who can help healthcare systems to assess them. The International Federation for Medical and Biological Engineering (IFMBE) is the global scientific society of biomedical engineers in official relations with the United Nations World Health Organisation (WHO) and has been very active in promoting the role of the biomedical engineer in Health Technology Assessment (HTA). The IFMBE Health Technology Assessment Division (HTAD) is the IFMBE operative branch in this field, promoting studies, projects and activities to foster the growth of this specific and very important science sector, including summer schools, training material, an HTA eLearning platform, HTA guidelines, awards and more. This article describes the vision, the mission and the strategy of the HTAD, with a focus on the results achieved and the impact this is having on global policymaking.\ud \ud

Automatic fall detection systems ensure that elderly people get prompt assistance after experiencing a fall. Fall detection systems based on accelerometer measurements are widely used because of their portability and low cost. However, the ability of these systems to differentiate falls from Activities of Daily Living (ADL) is still not acceptable for everyday usage at a large scale. More work is still needed to raise the performance of these systems. In our research, we explored an essential but often neglected part of accelerometer-based fall detection systems—data segmentation. The aim of our work was to explore how different configurations of windows for data segmentation affect detection accuracy of a fall detection system and to find the best-performing configuration. For this purpose, we designed a testing environment for fall detection based on a Support Vector Machine (SVM) classifier and evaluated the influence of the number and duration of segmentation windows on the overall detection accuracy. Thereby, an event-centered approach for data segmentation was used, where windows are set relative to a potential fall event detected in the input data. Fall and ADL data records from three publicly available datasets were utilized for the test. We found that a configuration of three sequential windows (pre-impact, impact, and post-impact) provided the highest detection accuracy on all three datasets. The best results were obtained when either a 0.5 s or a 1 s long impact window was used, combined with pre- and post-impact windows of 3.5 s or 3.75 s.

Background The effectiveness of electrochemotherapy of tumors (ECT) and of irreversible electroporation ablation (IRE) depends on different mechanisms and delivery protocols. Both therapies exploit the phenomenon of electroporation of the cell membrane achieved by the exposure of the cells to a series of high-voltage electric pulses. Electroporation can be fine-tuned to be either reversible or irreversible, causing the cells to either survive the exposure (in ECT) or not (in IRE), respectively. For treatment of tissues located close to the heart (e.g., in the liver), the safety of electroporation-based therapies is ensured by synchronizing the electric pulses with the electrocardiogram. However, the use of ECT and IRE remains contraindicated for patients with implanted cardiac pacemakers if the treated tissues are located close to the heart or the pacemaker. In this study, two questions are addressed: can the electroporation pulses interfere with the pacemaker; and, can the metallic housing of the pacemaker modify the distribution of electric field in the tissue sufficiently to affect the effectiveness and safety of the therapy? Results The electroporation pulses induced significant changes in the pacemaker ventricular pacing pulse only for the electroporation pulses delivered during the pacing pulse itself. No residual effects were observed on the pacing pulses following the electroporation pulses for all tested experimental conditions. The results of numerical modeling indicate that the presence of metal-encased pacemaker in immediate vicinity of the treatment zone should not impair the intended effectiveness of ECT or IRE even when the casing is in direct contact with one of the active electrodes. Nevertheless, the contact between the casing and the active electrode should be avoided due to significant tissue heating at the site of the other active electrode for the IRE protocol and may cause the pulse generator to fail to deliver the pulses due to excessive current draw. Conclusions The observed effects of electroporation pulses delivered in close vicinity of the pacemaker or its electrodes do not indicate adverse consequences for either the function of the pacemaker or the treatment outcome. These findings should contribute to making electroporation-based treatments accessible also to patients with implanted cardiac pacemakers.

Around the world, there are varieties of healthcare systems, each with its own characteristics and organizational structure according to national resources, requirements, and needs. Bearing this in mind it is very difficult to give a general definition for the healthcare system. Basically, it can be defined as a normatively accepted system of society and government in protecting and improving the population health, with all system factors affecting organized and constantly evolving as part of a general country social system. Each healthcare system consists of medical institutions which in addition to personnel and infrastructure must possess the necessary equipment in order to perform the correct diagnosis and treatment of their patients. In addition to the knowledge and experience of medical doctors, inpatient diagnosis and treatment, it is necessary to have the correct and tested medical apparatus. Diversity and innovativeness of medical devices, as a result of the evolving field of biomedical engineering, significantly contribute to improvement in quality and efficiency of healthcare services

Cell exposure to high-voltage, short-duration electric pulses can lead to temporary formation of hydrophilic pores in the plasma membrane and an increase in the membrane's permeability which consequently increases the transmembrane transport of molecules that are otherwise unable to cross the membrane. This phenomenon, termed membrane electroporation, is currently an applicable technique in different areas such as biomedicine, biotechnology, food technology and environmental applications. Electroporation pulses are generated by pulse power generators known as electroporators and delivered to the cells (in tissue) via electrodes. The objective of this paper is to review and compare characteristics of electroporation applications and equipment described in the literature and/or present on the market. Since there are no specific standards or regulations that specifically refer to the safety of medical devices with intended medical uses for electroporation, we propose guidelines for the design of clinical electroporators and define minimal requirements for their safe and efficient use which can be incorporated within the particular standards in the future. In order to facilitate the comparison of data obtained by different research groups and to enable reproduction of results under the same conditions, we want to stress the necessity of defining the electroporator's output parameters and tolerances of electroporation parameters for electroporation- based therapies.

Falls can have a major impact on physical and psychological health on elderly people who experience them. To reduce the negative consequences of a fall event, automatic fall detection systems are being developed to correctly identify when a person falls and alert the caregivers to provide assistance on time. Performance of fall detection algorithms is tested with datasets containing measurements of falls and regular activities of daily living. In this work we acquired fall signals with accelerometer sensors and compared them with digitized fall signal records from 6 different datasets. Additionally, three threshold-based algorithms for fall detection were implemented and their performance was tested with the analyzed datasets. The results suggest that a heterogeneity among the fall data in distinct datasets exist and that it affects the performance measures of tested datasets.

Continuous glucose monitor (CGM) is a wearable body sensor device that automatically measures glucose at regular intervals. CGM records can be used to analyze data after the collection or for predicting certain trends in the records in real-time. Nevertheless, missing values are common in CGM records. In this paper we discuss possible methods to replace the missing values in short-length gaps, in both real-time and after the collection use.

Electrochemotherapy (ECT) consists of administration of a chemotherapeutic drug followed by local application of high-voltage electroporation (EP) pulses and is a well-proven method for treatment of various types of tumors. However, as a precaution ECT of deep-seated internal tumors is contraindicated in patients with implanted cardiac pacemakers. To address this limitation a functioning pacemaker programmed in asynchronous D00 mode with the ventricular and atrial leads connected was exposed to EP pulses in a conductive medium mimicking the conditions encountered in clinical setting. EP pulses were generated by the Cliniporator Vitae device and delivered via electrodes for clinical ECT. Application of EP pulses was synchronized with different phases of the pacing cycle, including the potentially most vulnerable phase, the pacing pulse itself. The effects on pacemaker operation were investigated by recording the voltages between the cathode and the anode of the bipolar ventricular lead. EP pulses induced large artefacts far exceeding the amplitude of the pacing pulse itself. This was followed by transiently disrupted shape of the remaining portion of the pacing pulse. However, all effects were strictly limited to this single pacing pulse. No effects at all were observed in subsequent pacing pulses. The pacemaker and its function remained completely immune to electroporation pulses delivered outside the pacing pulse itself.

In this paper, we present our efforts towards more personalized diabetes treatment using the mobile application. The application helps to overcome the problem of missing and inaccurate data on blood glucose level, therapy, physical activity and other parameters, and allows development of the algorithms based on daily data of diabetic patients. For the purpose of our research, we developed two devices: myGluco - a small, portable device to be included into the glucose measurement kit patients carry with them on daily basis intended to transfer the saved blood glucose data from the glucose meter to the diabetic patients monitoring platform, and myWrist – the second small, portable device to track patients’ physical activity level and to serve in guiding the patients in performing strength exercises and to enable recording of their performance during exercising.

Biomedicinsko inženjerstvo značajno je doprinijelo promjenama u zdravstvenoj zaštiti i medicini, pa i ostalim biomedicinskim znanostima. Medi-cina i zdravstvena zaštita ovise o visokoj tehnologiji za prevenciju, dijagnosti-ku i liječenje bolesti, te za rehabilitaciju pacijenata. Biomedicinsko inženjer-stvo predstavlja jedno (od dvije) najbrže rastuće grane industrije u razvijenom svijetu, temeljeno na inovacijama što pokazuju statistike Europskog patentnog zavoda prema kojima je čitavo desetljeće broj patentnih prijava upravo najvi-še u području medicinske tehnologije. Razvoj biomedicinskog inženjerstva u Hrvatskoj započeo je institucionalno početkom sedamdesetih godina prošlog stoljeća, a nosioci razvoja bili su Elektrotehnički fakultet (danas Fakultet elektrotehnike i računarstva) i Fakultet strojarstva i brodogradnje Sveučilišta u Zagrebu. U ovom radu dan je prikaz dijela istraživačkih i inženjerskih do-stignuća njihovih istraživačkih timova u proteklim desetljećima.

Diabetes is one of the leading health problems in the world and its treatment typically requires a lot of interactions between healthcare professionals and patients. Patients are advised to self-monitor their blood glucose in order to achieve a specific level of glycemic control, to prevent hypoglycemia and to help healthcare professionals to adjust their treatment. In order to help patients and healthcare professionals provide better self- management and management of diabetes, we have developed new system. The system comprises a device for connecting and communicating with glucose meters, data management software for data acquisition and visualization, and database. The system is endorsed through the pilot project by Croatian Health Insurance Fund and Croatian Ministry of Health. We present some features of the collected data from the first one hundred patients.

Falls among the elderly are an important health issue which can lead to serious consequences. Unintentional falls in the elderly are the most common cause of nonfatal injuries. Different algorithms have been proposed for fall detection using vision based, ambient or inertial sensors. In this experiment, we used data collected from 16 subjects performing 15 tasks: 12 activities of daily living and 3 simulated falls. Subjects were equipped with a waist-mounted IMU to collect tri-axial accelerometer data during the activities. We derived features from accelerometer data on time-windowed identified activities and divided them into 2 different feature vectors (FV) that are used for fall detection algorithm. The selection was made based on the computational complexity of the features. We used different machine learning (ML) techniques to distinguish fall events from non-fall events (i.e. activities of daily living). In this paper, we compared and analyzed the accuracy of fall detection for different ML-based algorithms using the two accelerations-derived feature vectors for potential real-time implementation. The accuracy of the selected models ranged from 80.1 to 90.0% for FV1 and from 87.2 to 98.6% for FV2. The support vector machines algorithm achieved the best performance with accuracy 98.6%, sensitivity 98.7% and specificity 98.6% for FV2.

Self-monitoring of blood glucose (SMBG) is the key activity in diabetes management. Patients are required to take measurements and act accordingly, while the physicians use measured data to adjust the therapy. Though the accuracy of individual glucose meters used for SMBG is limited, the main difficulty in interpretation of the recorded data is due to inaccuracy of the records made by patients themselves into the paper diabetic diary. Oftentimes, patients do not record data properly and therefore the data is not reliable for use in determining long-term changes and trends or to use it for further analysis. Therefore, analysis and decision making should rely on the values recorded and stored in glucose memory. The large variety of glucometer models on the market introduce a large problem in using the recorded values since companies which produce and sale glucometers do not necessarily base their data transmission code on accepted standards but they embed custom made code. Data from 37 models of glucometers is transferred into a cloud based platform using previously developed system and available for immediate analysis and for saving into an appropriate health registry in a harmonized structure despite differences in protocols and data structure of different meters. Immediate statistics are given to the physicians upon patient’s checkup. However, general statistical metrics usually do not include metrics on glucose variability, which is one of the most important measurements of glycemic control. We added glycemic variability metrics, including other metrics into tool for data analysis using MATLAB. The output of the analysis can be stored in the system and can be combined with the existing healthcare registries to develop multidimensional analysis for new knowledge discovery. This paper describes the system for acquisition of SMBG data, MATLAB analysis software and the notes on the analysis of the previously discussed data set.

Pulse transit time (PTT) is promising for various clinical applications. This paper attempts to discuss different terminologies used for PTT and reveals the research discontinuity among different groups, with the aim to describe the definition of PTT and propose solutions to clarify the usage of PTT.

Electrocardiographs are nowadays standard part of diagnostic procedure in healthcare systems since they have high significance in diagnosis of large number of diseases and disorders. Due to development of technology, especially electronics, these devices have been revolutionized since the first prototype was invented. Nowadays, these devices are able to perform automated diagnosis and measure multiple parameters at once. Multiple international standards define device life circle, from production to disposal. However, this sophistication of ECG devices raises numerous questions regarding safety and accuracy. This chapter describes basic principles of electrocardiography and ECG devices as well as gives overview of requirements in area of safety and performance inspection of these devices.

Medical technology has radically reshaped the way healthcare is delivered today and continues to improve it in an accelerated pace. Biomedical Engineering (BME) is a multidisciplinary field lying in the cross-section of medical/biological sciences and engineering. Healthcare today is technology-driven and delivered by teams rather than individuals. Biomedical Engineers (BMEs) as professionals are playing a vital role in these developments, being behind the recent advances and involved during the whole life cycle of Medical Devices (MDs), from the innovative idea to their final use. More than five hundred thousand MDs models are available in the world market today. As a result, the BME profession is expected to be the first in demand amongst all other engineering subspecialties in the years to come. However, this rapid evolution creates a constant pressure for new knowledge and skills for the BMEs and therefore for continuous curriculum updates in order to meet R&D and market demands, but also for harmonisation of studies worldwide that will facilitate staff and students’ mobility and collaboration.

The aim of this study was the development of a geometrically simple and highly computationally-efficient two dimensional (2D) biophysical model of whole heart electrical activity, incorporating spontaneous activation of the sinoatrial node (SAN), the specialized conduction system, and realistic surface ECG morphology computed on the torso. The FitzHugh-Nagumo (FHN) equations were incorporated into a bidomain finite element model of cardiac electrical activity, which was comprised of a simplified geometry of the whole heart with the blood cavities, the lungs and the torso as an extracellular volume conductor. To model the ECG, we placed four electrodes on the surface of the torso to simulate three Einthoven leads VI, VII and VIII from the standard 12-lead system. The 2D model was able to reconstruct ECG morphology on the torso from action potentials generated at various regions of the heart, including the sinoatrial node, atria, atrioventricular node, His bundle, bundle branches, Purkinje fibers, and ventricles. Our 2D cardiac model offers a good compromise between computational load and model complexity, and can be used as a first step towards three dimensional (3D) ECG models with more complex, precise and accurate geometry of anatomical structures, to investigate the effect of various cardiac electrophysiological parameters on ECG morphology.

In order to achieve better self-control of their diabetes and to decrease long-term risks of complications, diabetic patients monitor several different parameters on a day-to-day basis. These parameters, such as blood glucose level, insulin intake, weight, diet, exercise and physical activity, blood pressure, can be easily acquired using IT technologies without oppressing the patient with handwritten diaries. At the same time, healthcare professionals are provided with the data on time and can intervene without delay, if necessary. The system collects data on blood glucose level using special device for communication between glucose meter and either a smartphone or a PC. A person’s weight is acquired using a modified body scale which, while weighing, at the same time scans patient’s feet and stores images for further processing and comparison with the images from pressure measurement platform. Patients enter their own diet and therapy using a smartphone app. Information on exercise and physical activity is provided using WBAN (Wireless Body Area Network) system with complementing software, both developed at our University. The system supports patients while performing previously determined exercise plan without the immediate presence of trainer, and also acquires data on regular daily activity (walking, running, sitting, …). The parts of the system providing some of the parameters are either developed in our previous studies or commercial, and they are integrated into our e- system. After collecting, the data is stored in a database for further use by diabetic patients themselves or by their healthcare providers.

In patients undergoing Coronary Artery Bypass Grafting (CABG) surgery postoperative atrial fibrillation (AF) occurs with prevalence of up to 40%. The highest incidence is between the second and third day after the operation. Following cardiac surgery AF causes various complications, hemodynamic instability, and can cause heart attack, cerebral and other thromboemolisms. AF increases morbidity, duration and expense of medical treatment. This study aims to identify patients at high risk of postoperative AF. An early prediction of AF would provide a timely prophylactic treatment and would reduce incidence of arrhythmia. Patients at low risk of postoperative AF could be excluded from the side effects of anti- arrhythmic drugs. The investigation included 50 patients in whom lead II electrocardiograms were continuously recorded for 48 hours following CABG. Univariate statistical analysis was used in the search of signal features that might predict AF. The most promising identified features were: P wave duration, RR interval duration and PQ segment level. On the basis of these a nonlinear multivariate prediction model was made deploying a Support Vector Machine (SVM) classifier. The prediction accuracy was found uprising over the time. At 48 hours following CABG ; the measured best average sensitivity was 95.9% and specificity 93.4%. The positive and negative predictive accuracy were 88.9% and 98.8%, respectively and the overall accuracy was 94.6%. In regard to the prediction accuracy, the risk assessment and prediction of postoperative AF are optimal to be done in the period between 24 and 48 hours following CABG.

The aim of this study is to develop a new, computationally-efficient, anatomically-realistic 3D bidomain cardiac electrical activity model using widely available software and standard low-cost hardware. The model incorporates whole-heart embedded in a human torso, spontaneous activation of sinoatrial node and specialized conduction system with heterogeneous action potential morphologies. The model is capable of generating realistic body surface electrocardiograms (ECGs) and is proposed as a useful tool for investigating some major issues in heart pathophysiology and in stimulation; such as simulating and optimizing synchronized electrical cardioversion, defibrillation and pacing stimulation.

The aim of this study is to develop a new, computationally-efficient, anatomically-realistic 3D bidomain cardiac electrical activity model using widely available software and standard low-cost hardware. The model incorporates whole-heart embedded in a human torso, spontaneous activation of sinoatrial node and specialized conduction system with heterogeneous action potential morphologies. The model is capable of generating realistic body surface electrocardiograms (ECGs) and is proposed as a useful tool for investigating some major issues in heart pathophysiology and in stimulation; such as simulating and optimizing synchronized electrical cardioversion, defibrillation and pacing stimulation., Cilj studije je razviti računalno efikasan, anatomski realističan 3D model električne aktivnosti cijelog ljudskog srca na široko dostupnoj računalnoj opremi. Model uključuje cijelo srce okruženo plućima i postavljeno unutar ljudskog torza, sa spontanom aktivacijom sinus-atrijskog čvora i specijaliziranim vodljivim putevima s heterogenim morfologijama akcijskih potencijala. Model omogućuje simuliranje elektrokardiograma (EKG) realističnog oblika te ga je moguće koristiti za istraživanje srčanih patofiziologija, simuliranje i optimizaciju sinkronizirane električne kardioverzije, defibrilacije ili simulacije različitih srčanih stimulacija.

In the past few years, usage of smartphones increased significantly because of their computational power, large screens, memory capacity, large number of embedded sensors and other features. The aim of this study is to explore, test and compare the quality of measuring human activities through acquisition of raw data from smartphone built-in accelerometer. In a series of experiments, acceleration measurements from different smartphones were compared to the accelerometer data from a custom made sensor node. The selected activities that were measured are: walking, walking up stairs, walking down stairs, brisk walking, running and sitting (as a state of inactivity). Signal processing was made in Matlab. After calculation and comparison of the magnitude of linear acceleration, Fast Fourier Transform (FFT) was calculated for each activity on 256 samples of the signal. Then the energy of each activity was calculated and compared. Results show that the recorded acceleration values and their variations of amplitude of linear acceleration for sitting is negligible, while the amplitudes for other activities (walking, walking up stairs, down stairs and running) are more significant. Also, the amplitudes of the running activity measured with the sensor node are considerably larger than amplitudes of all other activities (walking, walking up stairs and walking down stairs). However, signals measured with smartphone introduced an error into calculation of linear acceleration because at least one of accelerometer axis from smartphone accelerometers was saturated for activities of greater intensity (brisk walking and running). Measurements using the accelerometer of the sensor node have shown larger differences between amplitudes of linear acceleration and differences between energy for each activity and the results of recordings can be used for measurements and not for monitoring applications only.

In recently studies, as one of simpler and better solution for measuring human mobility and physical activity, Wireless Body Area Networks (WBAN) have been introduced. In order to acquire those information and due to the desire of future growth in mentioned filed, WBAN consisting of inertial and magnetic sensors was developed at our Department. The WBAN together with developed desktop application forms a unique system for assisted exercising and exercise evaluation. In exercising evaluation of patients or sportsmen, a new approach in qualitative assessment is used. New approach introduces “Exercise Signature” as a reference signal for evaluation of exercising. The main concept is that every exercise has some characteristic data which are calculated by the developed algorithm and then saved in exercise database. The mentioned application is not only used for calculating characteristic exercise data, but it also has a role in visualization of the virtual trainer which leads the person who is exercising through his personalized training. In this work, we present detailed description of the whole assisted strength exercising system and elaborate its possible applications. Endurance exercising protocols will be described elsewhere.

Human motion tracking has an important role in a wide variety of applications, including physical exercise. Exercise tracking systems based on the combined use of inertial and magnetic sensors (also called IMU systems) have witnessed a fast increase in popularity in recent years due to their high accuracy and portability. Nonetheless, a complete solution that would guide a user in correctly performing a movement and provide a real-time evaluation of the performed movement is still not available. This paper presents an IMU based system for human motion tracking and its application in real-time evaluation of repetitive physical exercise. The user is provided with a visual demonstration of the correct exercise execution and his own movements. An algorithm is used to compare the movements, thus enabling quantitative and qualitative exercise assessment. However, only simple exercises (that include one limb motion) have been tested with this system, and evaluation of more complex movements shall be explored in the future.

This paper presents a virtual reality system for assisted exercise using Wireless Body Area Network (WBAN). Sensor nodes with integrated accelerometer, gyroscope and magnetometer are used for orientation-driven visualization of human body motion. A virtual scene is created using Unity 3D game-engine. The scene involves virtual trainer for providing the visual guidance during exercise, and user’s avatar for realtime tracking of the user’s motion. The user is given direct feedback while exercising in form of textual and audio messages. Qualitative and quantitative assessment of the performance of each exercise is retrieved through the network. The application is deployed for use on mobile devices (e.g. smartphones, tablets) and PCs. © Springer International Publishing Switzerland 2015.

In this paper we present the calculation of current transients as a response to the applied voltage for a biological tissue whose complex permittivity was modelled by four Cole-Cole type dispersions. Initial formulation in the Laplace domain was transformed to the time domain by numerical inversion of Laplace transform using Stehfest algorithm. We analysed the influence of the voltage generator rise time and internal resistance on the current transient. Moreover, we analysed contributions of each individual dispersion on the current waveform. Due to its simplicity and good performance, Stehfest algorithm proved to be a very good choice for current transient calculation for multi Cole-Cole type dispersion materials like biological tissues.

Human balance control system allows people to independently perform acts of daily living and to avoid falls that can cause injuries and hospitalization. Aging or various pathologies may cause disorders in the balance system and result in wide variety of problems and generally decreased quality of life. Researchers and health professionals therefore strive to develop effective methods and instruments for prompt diagnosis and rehabilitation of balance disorders. A common approach used to detect balance problems in scientific studies and clinical applications is to analyze various parameters of postural stability gathered during quiet stance. This paper presents an experimental setting for postural stability evaluation composed of two independent systems. A commercial force platform (Ecowalk) and a sensor node with multiple inertial and magnetic sensors are combined to simultaneously measure trunk orientation and center-of-pressure (COP) during quiet stance. A preliminary study with 8 healthy subjects was conducted in order to test the system functionality. Trunk orientation and COP were measured in four different conditions for every subject as they tried to maintain steady upright position. The area of trunk sway trajectory and COP variability were calculated from orientation and force platform measurements. The goal of this study was to explore whether use of the created experimental setting can provide a measure of two different biomechanical properties related to the balance control system during quiet stance trials. The initial results are promising as they have shown consistency in both variables during trials in different conditions, but further measurements with more subjects are needed for stronger conclusions.

Biomedical Engineering programs are present at a large number of universities all over the world with an increasing trend. New generations of biomedical engineers have to face the challenges of health care systems round the world which need a large number of professionals not only to support the present technology in the health care system but to develop new devices and services. Health care stakeholders would like to have innovative solutions directed towards solving problems of the world growing incidence of chronic disease and ageing population. These new solutions have to meet the requirements for continuous monitoring, support or care outside clinical settlements. Presence of these needs can be tracked through data from the Labor Organization in the U.S. showing that biomedical engineering jobs have the largest growth at the engineering labor market with expected 72% growth rate in the period from 2008-2018. In European Union the number of patents (i.e. innovation) is the highest in the category of biomedical technology. Biomedical engineering curricula have to adopt to the new needs and for expectations of the future. In this paper we want to give an overview of engineering professions in related to engineering in medicine and biology and the current status of BME education in some regions, as a base for further discussions.

Strong electrical stimulation pulses are needed for activation of the brain motor area during general anaesthesia in cases with the intact patient’s head mostly because of high skull and scalp impedance. In transcranial electrical stimulation, two types of electrodes with small area are used in order to enable selective neural stimulation: Ag–AgCl cup EEG electrodes and stainless steel corkscrew electrodes. The influence of pulse current stimuli parameters on the characteristics of cup EEG and corkscrew electrodes at high current density was investigated. In contrast to the corkscrew electrodes that showed nearly linear behaviour, the cup electrodes showed non-linear properties, i.e. a significant increase in pulse voltage to current ratio at high current density. The design of a microprocessor-based transcranial stimulator, enabling fast setting of stimulation parameters due to the implemented fast measurement circuits and a multidimensional look-up table is described.

In contrast with other professional organizations, which are membership based, the IFMBE is a federation that forms an umbrella to unite many national and trans-national societies. Except for a small number of individuals who are members of its International Academy and very few members from countries that do not have an organized society, IFMBE does not have individual members. This presents the first major challenge to the Federation namely, identifying individuals who will devote time and effort to the organization. We have been very fortunate in the past.