A Recursive-Memory Brain-State Classifier with 32-Channel Track-and-Zoom Δ2Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators

📋 论文概要

该论文提出了一种用于闭环神经调控的递归记忆脑状态分类器，集成了32通道Track-and-Zoom Δ2Σ ADC和电荷平衡可编程波形刺激器。解决了在神经刺激期间不间断监测脑活动、高效自适应处理以及安全刺激的挑战。

💡 主要创新点

• 提出递归记忆脑状态分类器架构，实现高效自适应神经刺激决策。
• 采用32通道Track-and-Zoom Δ2Σ ADC，在刺激期间连续监测脑信号。
• 集成电荷平衡可编程波形刺激器，提供丰富时空刺激模式并确保安全。

🏷 关键词

📄 原文摘要

David Groppe2, Taufik A. Valiante3, Naveen Verma4, Roman Genov1 University of Toronto, Toronto, Canada Krembil Neuroscience Center, Toronto, Canada 3 Toronto Western Hospital, Toronto, Canada 4 Princeton University, Princeton, NJ 1 2 The advancement of closed-loop neuromodulation for treating neurological disorders demands: (1) analog circuits monitoring the brain activity uninterruptedly even during neurostimulation, (2) energy-efficient high-efficacy processors for responsive, adaptive, personalized neurostimulation, and (3) safe neurostimulation paradigms with rich spatio-temporal stimuli for controlling the brain’s complex dynamics. This paper presents an implantable neural interface processor (NURIP) that addresses these requirements - it performs brain state classification for reliable seizure prediction and contingent seizure abortion. As shown in Fig. 17.9.1 (center) NURIP includes 32 bidirectional channels, each

👥 作者与机构

Gerard O'Leary1, M. Reza Pazhouhandeh1, Michael Chang1,