An Implantable Neuromorphic Sensing System Featuring Near-Sensor Computation and Send-on-Delta Transmission for Wireless Neural Sensing of

Abstract

This article presents a bioinspired, event-driven neuromorphic sensing system (NSS) capable of performing on-chip feature extraction and “se nd-on-delta” pulse-based trans- mission, targeting peripheral nerve neural recording applications. The proposed NSS employs event-based sampling which, by lever- aging the sparse nature of electroneurogram (ENG) signals, achieves a data compression ratio of >125×, while maintaining a low normalized rms error (NRMSE) of 4% after reconstruction. The proposed NSS consists of three sub-circuits. A clockless level- crossing (LC) analog-to-digital converter (ADC) with background offset calibration has been employed to reduce the data rate, while maintaining a high signal to quantization noise ratio (SQNR). A fully synthesized spiking neural network (SNN) extracts temporal features of compound action potential (CAP) signals and consumes only 13 µW. An event-driven, pulse- based body channel communication (Pulse-BCC) with serialized address-event representation (AER) encoding schemes minimizes transmission energy and form factor. The prototype is fabricated in 40-nm CMOS occupying a 0.32-mm 2 active area and consumes in total 28.2 and 50 µW power in feature extraction and full Manuscript received 31 January 2022; revised 21 April 2022 and 10 June 2022; accepted 14 July 2022. Date of current version 26 September 2022. This article was approved by Associate Editor Shouyi Yin. This work was supported in part by the European Research Council (ERC) t