@inproceedings{5d494e331adb4bdaaf27ede0ecd0cc34,
title = "A 1024-Channel 268 nW/pixel 36x36 μm2/ch Data-Compressive Neural Recording IC for High-Bandwidth Brain-Computer Interfaces",
abstract = "This paper presents a neural recording IC featuring lossy compression during digitization, thus preventing data deluge and enabling a compact active digital pixel design. The wired-OR-based compression discards unwanted baseline samples while allowing the reconstruction of spike samples. The IC features a 32x32 MEA with 36 μ m pixel pitch and consumes 268nW per pixel from a single 1V supply. It achieves 9.8 μ VRMS input-referred noise and 0.3-5kHz bandwidth, resulting in NEF/PEF of 3.7/14.1. ",
keywords = "brain, compression, interface, neural, recording",
author = "Jang, {Moon Hyung} and Wei-Han Yu and Changuk Lee and Maddy Hays and Pingyu Wang and Nick Vitale and Pulkit Tandon and Youngcheol Chae and Muratore, {Dante G.} and {More Authors}",
note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. ; 2023 IEEE Symposium on VLSI Technology and Circuits, VLSI Technology and Circuits 2023 ; Conference date: 11-06-2023 Through 16-06-2023",
year = "2023",
doi = "10.23919/VLSITechnologyandCir57934.2023.10185288",
language = "English",
isbn = "979-8-3503-4669-5",
series = "Digest of Technical Papers - Symposium on VLSI Technology",
publisher = "IEEE",
booktitle = "Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits, VLSI Technology and Circuits 2023",
address = "United States",
}