Pervasive Real-Time Biomedical Monitoring System

With the tremendous advancements in low cost, power efficient hardware and the recent interest in biomedical embedded systems, numerous traditional biomedical systems can be replaced with smaller embedded systems that do real-time analysis to provide bin-feedback to the users. This paper presents a prototype of an embedded system which is capable of real-time data collection, using analog and digital sensors and processing, to compute physiological variables and metrics. These metrics in turn can be used to determine information about the user's general well being. The sensors provide motion, brain wave activity (EEG) and blood oxygenation (SpO(2)) information. The system presented automatically computes the application specific metrics and indicates the results of the detection scheme to the user and to a monitoring base station. The metrics being used have been validated using raw data from patients suffering epileptic seizures and from past research. The paper also deals with application scenarios for such systems and architecture for an FPGA based implementation is discussed.