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

Himanshu Markandeya, Georgios Karakonstantis, Shriram Raghunathan, Pedro Irazoqui, Kaushik Roy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationISLPED'10 - Proceedings of the 16th ACM/IEEE International Symposium on Low-Power Electronics and Design
Pages301-306
Number of pages6
DOIs
StatePublished - 2010
Externally publishedYes
Event16th ACM/IEEE International Symposium on Low-Power Electronics and Design, ISLPED'10 - Austin, TX, United States
Duration: Aug 18 2010Aug 20 2010

Publication series

NameProceedings of the International Symposium on Low Power Electronics and Design
ISSN (Print)1533-4678

Conference

Conference16th ACM/IEEE International Symposium on Low-Power Electronics and Design, ISLPED'10
Country/TerritoryUnited States
CityAustin, TX
Period8/18/108/20/10

Keywords

  • Biomedical
  • Epilepsy
  • Low power
  • Seizure detection

ASJC Scopus subject areas

  • General Engineering

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