Skip to main navigation Skip to search Skip to main content

A 256-Channel, 3.49-mW Wireless Neural Recording SoC with Adaptive Delta Compression and Error-Resilient Coding

  • Wenxian Gu
  • , Liangjian Lyu*
  • , Zepeng Huang
  • , Yingfei Xiang
  • , Sirou Li
  • , Wenjun Gong
  • , Xing Wu
  • , C. J.Richard Shi
  • *Corresponding author for this work
  • East China Normal University
  • Fudan University
  • University of Washington

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents a fully-integrated 256-channel wireless wideband neural-recording SoC that integrates AFEs with distributed neural processors and a low-power bidirectional transceiver. A nearlossless adaptive-delta algorithm reduces data rate by 60% while preserving features. A power-efficient tri-state bus enables streamlined transfer. The 3.2 GHz/433 MHz OOK links with hybrid error-resilient coding boost reliability. Fabricated in 65 nm CMOS, this SoC consumes 3.49 mW at 1.2 V and supports 30 kHz/channel.

Original languageEnglish
Title of host publication2026 IEEE Custom Integrated Circuits Conference, CICC 2026 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331572105
DOIs
StatePublished - 2026
Event46th Annual IEEE Custom Integrated Circuits Conference, CICC 2026 - Seattle, United States
Duration: 19 Apr 2026 → 23 Apr 2026

Publication series

NameProceedings of the Custom Integrated Circuits Conference
ISSN (Print)0886-5930

Conference

Conference46th Annual IEEE Custom Integrated Circuits Conference, CICC 2026
Country/TerritoryUnited States
CitySeattle
Period19/04/26 → 23/04/26

Keywords

  • adaptive-delta compression
  • bidirectional wireless transceiver
  • error-resilient coding
  • tri-state bus
  • wideband neural recording

Fingerprint

Dive into the research topics of 'A 256-Channel, 3.49-mW Wireless Neural Recording SoC with Adaptive Delta Compression and Error-Resilient Coding'. Together they form a unique fingerprint.

Cite this