A 97 fJ/Conversion Neuron-ADC with Reconfigurable Sampling and Static Power Reduction

TL;DR

This paper presents a bio-inspired Neuron-ADC that uses level-crossing sampling and a refractory circuit to efficiently convert bio-signals into digital spikes, achieving low power consumption and reconfigurable sampling for biomedical applications.

Contribution

It introduces a novel Neuron-ADC design with reconfigurable sampling and static power reduction techniques, improving energy efficiency and adaptability for bio-signal processing.

Findings

Achieves a maximum ENOB of 6.9 bits

Attains a FoM of 97 fJ/conversion

Reduces static power by up to 41.1%

Abstract

A bio-inspired Neuron-ADC with reconfigurable sampling and static power reduction for biomedical applications is proposed in this work. The Neuron-ADC leverages level-crossing sampling and a bio-inspired refractory circuit to compressively converts bio-signal to digital spikes and information-of-interest. The proposed design can not only avoid dissipating ADC energy on unnecessary data but also achieve reconfigurable sampling, making it appropriate for either low power operation or high accuracy conversion when dealing with various kinds of bio-signals. Moreover, the proposed dynamic comparator can reduce static power up to 41.1% when tested with a 10 kHz sinusoidal input. Simulation results of 40 nm CMOS process show that the Neuron-ADC achieves a maximum ENOB of 6.9 bits with a corresponding FoM of 97 fJ/conversion under 0.6 V supply voltage.