A 259.6 mu W HRV-EEG Processor With Nonlinear Chaotic Analysis During Mental Tasks

Abstract

A system-on-chip (SoC) with nonlinear chaotic analysis (NCA) is presented for mental task monitoring. The proposed processor treats both heart rate variability (HRV) and electroencephalography (EEG). An independent component analysis (ICA) accelerator decreases the error of HRV extraction from 5.94% to 1.84% in the preprocessing step. Largest Lyapunov exponents (LLE), as well as linear features such as mean and standard variation and sub-band power, are calculated with NCA acceleration. Measurements with mental task protocols result in confidence level of 95%. Thanks to the hardware acceleration, the chaos-processor fabricated in 0.13 mu m CMOS technology consumes only 259.6 mu W.