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

Yuming He, Federico Corradi, Chengyao Shi, Stan van der Ven, Martijn Timmermans, Jan Stuijt, Paul Detterer, Pieter Harpe, Lucas Lindeboom, Evelien Hermeling, Geert Langereis, Elisabetta Chicca, Yao-Hong Liu

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This paper presents a bio-inspired event-driven neuromorphic sensing system (NSS) capable of performing on-chip feature extraction and "send-on-delta" pulse-based transmission, targeting peripheral-nerve neural recording applications. The proposed NSS employs event-based sampling which, by leveraging the sparse nature of electroneurogram (ENG) signals, achieves a data compression ratio of >125×, while maintaining a low normalized RMS error of 4% after reconstruction. The proposed NSS consists of three sub-circuits. A clockless level-crossing (LC) ADC with background offset calibration has been employed to reduce the data rate, while maintaining a high signal to quantization noise ratio. A fully synthesized spiking neural network (SNN) extracts temporal features of compound action potential signals consumes only 13 μW. An event-driven pulse-based body channel communication (Pulse-BCC) with serialized address-event representation encoding (AER) schemes minimizes transmission energy and form factor. The prototype is fabricated in 40-nm CMOS occupying a 0.32-mm2 active area and consumes in total 28.2 μW and 50 μW power in feature extraction and full diagnosis mode, respectively. The presented NSS also extracts temporal features of compound action potential signals with 10-μs precision.

Original languageEnglish
Pages (from-to)3058-3070
Number of pages13
JournalIEEE Journal of Solid-State Circuits
Volume57
Issue number10
DOIs
Publication statusPublished - Oct 2022
Externally publishedYes

Keywords

  • sensors
  • implants
  • neurons
  • wireless communication

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