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一种用于运动预测的耐光无线神经记录集成电路,具备基于近红外的电源和数据遥测功能。

A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry.

作者信息

Lim Jongyup, Lee Jungho, Moon Eunseong, Barrow Michael, Atzeni Gabriele, Letner Joseph G, Costello Joseph T, Nason Samuel R, Patel Paras R, Sun Yi, Patil Parag G, Kim Hun-Seok, Chestek Cynthia A, Phillips Jamie, Blaauw David, Sylvester Dennis, Jang Taekwang

机构信息

Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA.

Department of Information Technology and Electrical Engineering, ETH Zürich, 8092 Zürich, Switzerland.

出版信息

IEEE J Solid-State Circuits. 2022 Apr;57(4):1061-1074. doi: 10.1109/jssc.2022.3141688. Epub 2022 Jan 25.

Abstract

Miniaturized and wireless near-infrared (NIR) based neural recorders with optical powering and data telemetry have been introduced as a promising approach for safe long-term monitoring with the smallest physical dimension among state-of-the-art standalone recorders. However, a main challenge for the NIR based neural recording ICs is to maintain robust operation in the presence of light-induced parasitic short circuit current from junction diodes. This is especially true when the signal currents are kept small to reduce power consumption. In this work, we present a light-tolerant and low-power neural recording IC for motor prediction that can fully function in up to 300 W/mm of light exposure. It achieves best-in-class power consumption of 0.57 W at 38° C with a 4.1 NEF pseudo-resistorless amplifier, an on-chip neural feature extractor, and individual mote level gain control. Applying the 20-channel pre-recorded neural signals of a monkey, the IC predicts finger position and velocity with correlation coefficient up to 0.870 and 0.569, respectively, with individual mote level gain control enabled. In addition, wireless measurement is demonstrated through optical power and data telemetry using a custom PV/LED GaAs chip wire bonded to the proposed IC.

摘要

基于近红外(NIR)的小型化无线神经记录器,具备光供电和数据遥测功能,已作为一种有前景的方法被引入,可在最先进的独立记录器中以最小的物理尺寸进行安全的长期监测。然而,基于NIR的神经记录集成电路面临的一个主要挑战是,在存在结二极管产生的光致寄生短路电流的情况下,要保持稳定运行。当信号电流保持较小时以降低功耗时,情况尤其如此。在这项工作中,我们展示了一种用于运动预测的耐光且低功耗的神经记录集成电路,它在高达300 W/mm的光照下仍能完全正常工作。通过一个4.1 NEF的伪无电阻放大器、片上神经特征提取器和单个节点级增益控制,该集成电路在38°C时实现了0.57 W的同类最佳功耗。应用猴子的20通道预记录神经信号,在启用单个节点级增益控制的情况下,该集成电路预测手指位置和速度的相关系数分别高达0.870和0.569。此外,通过使用定制的PV/LED砷化镓芯片与所提出的集成电路进行引线键合,通过光供电和数据遥测展示了无线测量。

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