In this article, the design and development aspects of a compact bio-potential measuring system, named ExGSense, is presented. Two versions of the prototype have been developed; first one can measure 3 + 1 V leads in time-multiplexed fashion, while the other can measure 3 + 1 V leads simultaneously. This article also presents an efficient algorithm for filtering electrocardiogram signals which is required to attenuate the effect of motion artefacts which are inevitable in wearable systems. Further, a user-friendly interface for PC and smartphone has also been developed. By the virtue of an ultra-low noise instrumentation amplifier and the programmability of gain and bandwidth of the bio-signal measuring system, a number of other bio-potential signals like EMG, EOG and EEG have been successfully recorded using disposable, off-the-shelf wet Ag/AgCl electrodes.

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A low power VLSI architecture implementing an algorithm for early seizure detection in epileptic patients using intracranial or scalp EEG data is proposed. The algorithm tested over more than 40 hours of recording from standard databases achieves a best-case result of 100% sensitivity at a false positive rate of 0.2 per hour. The algorithm is programmed on an FPGA and was experimentally validated along with a neural recording SoC chip to demonstrate a real-time seizure detection microsystem.