PW

Pingyu Wang

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2 records found

Conference paper (2023) - Moon Hyung Jang, Wei-Han Yu, Changuk Lee, Maddy Hays, Pingyu Wang, Nick Vitale, Pulkit Tandon, Youngcheol Chae, Dante G. Muratore, More authors...
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. ...
Journal article (2023) - Moonhyung Jang, Maddy Hays, Changuk Lee, Pietro Caragiulo, Athanasios T. Ramkaj, Pingyu Wang, Nicholas Vitale, Pulkit Tandon, Dante G. Muratore, More authors...
This article presents a data-compressive neural recording IC for single-cell resolution high-bandwidth brain–computer interfaces (BCIs). The IC features wired-OR lossy compression during digitization, thus preventing data deluge and massive data movement. By discarding unwanted baseline samples of the neural signals, the output data rate is reduced by 146× on average while allowing the reconstruction of spike samples. The recording array consists of pulse-position modulation (PPM)-based active digital pixels (ADPs) with a global single-slope (SS) analog-to-digital conversion scheme, which enables a low-power and compact pixel design with significantly simple routing and low array readout energy. Fabricated in a 28-nm CMOS process, the neural recording IC features 1024 channels (i.e., 32 × 32 array) with a pixel pitch of 36 µm that can be directly matched to a high-density micro-electrode array (MEA). The pixel achieves 7.4-µVrms input-referred noise with a −3-dB bandwidth of 300 Hz–5 kHz while consuming only 268 nW from a single 1-V supply. The IC achieves the smallest area per channel (36 × 36 µm2) and the highest energy efficiency among the state-of-the-art neural recording ICs published to date. ...