A 256-Channel 0.227µJ/class Versatile Brain Activity Classification and Closed-Loop Neuromodulation SoC with 0.004mm<sup>2</sup>-1.51 µW/channel Fast-Settling Highly Multiplexed Mixed-Signal Front-End-Reference-Cited by-同舟云学术

A 256-Channel 0.227µJ/class Versatile Brain Activity Classification and Closed-Loop Neuromodulation SoC with 0.004mm²-1.51 µW/channel Fast-Settling Highly Multiplexed Mixed-Signal Front-End

Published:2022-02-20 Issue: Volume: Page:
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Container-title:2022 IEEE International Solid- State Circuits Conference (ISSCC)
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Author:

Shin Uisub¹,Somappa Laxmeesha¹,Ding Cong¹,Vyza Yashwanth¹,Zhu Bingzhao¹,Trouillet Alix¹,Lacour Stephanie P.¹,Shoaran Mahsa¹

Affiliation:

1. EPFL,Lausanne,Switzerland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9731529/9731102/09731776.pdf?arnumber=9731776

Reference12 articles.

1. 26.3 A Closed-Loop Neuromodulation Chipset with 2-Level Classification Achieving 1.5Vpp CM Interference Tolerance, 35dB Stimulation Artifact Rejection in 0.5ms and 97.8% Sensitivity Seizure Detection

2. A Recursive-Memory Brain-State Classifier with 32-Channel Track-and-Zoom ?2? and Charge-Balanced Programmable Waveform Neurostimulators;o'leary;ISSCC Dig Tech Papers,2018

3. 26.2 A Neuromorphic Multiplier-Less Bit-Serial Weight-Memory-Optimized 1024-Tree Brain-State Classifier and Neuromodulation SoC with an 8-Channel Noise-Shaping SAR ADC Array

4. A Single-Chip Bidirectional Neural Interface With High-Voltage Stimulation and Adaptive Artifact Cancellation in Standard CMOS

5. A Fully Integrated 16-Channel Closed-Loop Neural-Prosthetic CMOS SoC With Wireless Power and Bidirectional Data Telemetry for Real-Time Efficient Human Epileptic Seizure Control

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