Abstract
In this article, we present a low-power, user-programmable architecture for discrete wavelet transform (DWT) based epileptic seizure detection algorithm. A simplified, low-pass filter (LPF)-only-DWT technique is employed in which energy contents of different frequency bands are obtained by subtracting quasi-averaged, consecutive LPF outputs. Training phase is used to identify the range of critical DWT coefficients that are in turn used to set patient-specific system level parameters for minimizing power consumption. The proposed optimizations allow the design to work at significantly lower power in the normal operation mode. The system has been tested on neural data obtained from kainate-treated rats. The design was implemented in TSMC-65nm technology and consumes less than 550-nW power at 250-mV supply.
Published Version
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