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.
|Title of host publication||Proceedings of the International Symposium on Low Power Electronics and Design|
|Number of pages||6|
|Publication status||Published - 01 Jan 2010|
Markandeya, H., Karakonstantis, G., Raghunathan, S., Irazoqui, P., & Roy, K. (2010). Low-power DWT-based quasi-averaging algorithm and architecture for epileptic seizure detection. In Proceedings of the International Symposium on Low Power Electronics and Design (pp. 301-306) https://doi.org/10.1145/1840845.1840907