Epilepsy is the commonest serious brain disorder, affecting 1-2% of the general population. Epileptic seizures are usually expressed with a wide range of paroxysmal recurring motor, cognitive, autonomic symptoms and EEG changes. Therefore reliable diagnosis requires state of the art monitoring and communication technologies providing real-time, accurate and continuous brain and body multi-parametric data measurements. The purpose of this paper is to present an adequate mobile system comprising all required sensor types for the everyday life monitoring of patients with epilepsy.

This paper proposes a processing architecture and a programming framework for the remote and seamless update of the algorithms used in the context of biomedical smart sensors. The generic processing architecture provides, among others, the following facilities to a Body Sensor Network in a seamless way to the user beyond functional modularity: 1) direct and immediate update with new and improved versions of the algorithms, 2) personalization of algorithms, 3) adaptability to the user context, 4) remote test of algorithms, 5) hardware reusability and sustainability, 6) parallel execution of several monitoring applications in one device, 7) structural modularity. Due to its simplicity, the proposed technique takes advantage over other solutions employed in applications that impose severe limitations on hardware/software resources of the devices, which may result in lower cost and size of them. The results obtained on two heart monitoring applications shows the viability of the proposed scheme.

For supporting rescue operations in disasters, vital data collections in wireless sensor networks have been proposed so far. In such systems, we can expect to predict each patient’s probability of survival based on real-time vital data. In this paper, we focus on prehospital care and propose a method to determine treatment plans and schedules of patients. The proposed method maximizes the number of expected saved patients under limited medical resources. This optimization problem is called Treatment Planning and Scheduling, which is NP-hard. Therefore, we propose a heuristic algorithm based on depth-limited search. We have compared the proposed method with greedy methods. The results show the proposed method can derive solutions in practical time and the average number of saved patients is 10% larger compared to the greedy methods.

The Functional Movement Screen(FMS) is a useful tool to assess functional abilities in a pre-participation screening. Its seven dynamic movement tests reveal shortcomings in stability and mobility and screen the whole body. However, the current test protocol delivers results that are subjective, qualitative and have to be manually processed. This article presents a semi-automatic system to overcome these limitations for the Deep Squat test. The system consists of four wireless inertial sensors and a central Android-based processing node for data analysis and result storage. We developed our system based on data from ten subjects and evaluated the results with the FMS scoring guidelines. The sensor-based scoring system completely agreed with the manual scoring in eight out of ten subjects. In addition, quantitative information in case of compensation movements was logged. Thus, our system is capable of simplifying the FMS test and enhances the score with objective, quantitive and automatic results.

For a new optical body area network (BAN) technique, a fundamental study was conducted of optical data transmission through a human body using diffusely scattered light. The frequency bandwidth for data transmission was restricted by the effect of strong scattering inside body tissues. In experiments using human bodies, the possibility of the transmission up to 100 MHz was confirmed. Using the linear equalization process, we can transmit an 800 MHz square wave signal. Data transmission of around 200 mm distance in a human hand was possible. To overcome problems of noise, multipath transmission, and the instantaneous interruption of data transmission, the space diversity (SD) technique was applied to stabilize data communications. The SD technique effectiveness was confirmed through analysis using real optical impulse responses. The feasibility of BAN using diffusely scattered light in the body was verified through these analyses.