A micropower EEG detection system applicable for paralyzed hand artifical control

Abstract

In this paper, Analog Front-End EEG system is designed. It consists of cascaded instrumentation amplifier (CIA), dual-notch low-pass filter (DNLPF), and programmable gain amplifier (PGA). The proposed CIA is voltage amplifier based on gyrator realized by two digitally programmable operational transconductance amplifiers (DPOTAs). It achieves 31dB gain besides providing high-pass feature. To minimize the effect of powerline interference, DNLPF is designed. Furthermore, it has low-pass feature to attenuate unwanted noise signal, and this offers compactness in term of chip area. PGA fortifies processed EEG signal with more gain. Its structure is built from master/slave paths to achieve high linearity. PSpice simulation results are carried out using 0.25-μm CMOS process and operating under ±0.8V. Simulation results for EEG system achieve controllable gain (61dB–84dB), input referred noise of 4μV/√Hz, and power dissipation of 32μW. As an EEG-oriented application, brain-computer interface (BCI) system is proposed to be used in paralyzed limb artificial control.