A low power charge mode compressive acquisition of multichannel EEG signals

Abstract

The limited power budget of a multiple sensor system such as a wireless body area network (WBAN) necessiates both power efficient sensing architecture and low power circuit implementation. A sparse recovery based sub-Nyquist signal acquisition technique called compressed sensing has been proposed recently, which enables lower power and lesser complexity in the sensing front end. In this work, a low power multichannel EEG signal acquisition system based on distributed compressed sensing has been proposed which performs simultaneous sensing and recovery of multiple sparse signals with compression ratios greater than an individual channel compression. Charge mode switched capacitor circuit techniques are employed to perform the core compressed sensing measurements to reduce power consumption. The system is implemented in a 1.8 V, 0.18 μm CMOS technology with a discrete time sampling based charge domain analog front-end. A single multiplexed 8-bit SAR ADC has been designed and integrated to digitize the measurements from all channels. The system has been tested with a set of EEG signals from practical neural recordings and the results show an average PSNR of 22.17 dB while sensing 64-channels simultaneously at a compression ratio (CR) of up to 1/4.