A 1.52 uJ/classification Patient-Specific Seizure Classification Processor using Linear SVM

Abstract

This paper presents an 8-channel electroencephalograph (EEG) classification processor for seizure detection and recording. To integrate 8 channels, an area- and energy-efficient filter architecture using Distributed Quad-LUT (DQ-LUT) is proposed, which reduces area by 64.2% with minimal overhead in power. delay product. The on-chip patient specific classification with a Linear Support-Vector Machine (SVM) results in 82.7% seizure detection accuracy with a 2 second latency using the CHB-MIT EEG database [1]. The overall energy efficiency is measured