Low-power DWT-based quasi-averaging algorithm and architecture for epileptic seizure detection

Authors:
Himanshu Markandeya;Georgios Karakonstantis;Shriram Raghunathan;Pedro Irazoqui;Kaushik Roy
Affiliations:
Purdue Univeristy, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA
Venue:
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Year:
2010

Citing 3
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Abstract

In this paper, we have developed a low-complexity algorithm for epileptic seizure detection with a high degree of accuracy. The algorithm has been designed to be feasibly implementable as battery-powered low-power implantable epileptic seizure detection system or epilepsy prosthesis. This is achieved by utilizing design optimization techniques at different levels of abstraction. Particularly, user-specific critical parameters are identified at the algorithmic level and are explicitly used along with multiplier-less implementations at the architecture level. The system has been tested on neural data obtained from in-vivo animal recordings and has been implemented in 90nm bulk-Si technology. The results show up to 90 % savings in power as compared to prevalent wavelet based seizure detection technique while achieving 97% average detection rate.