基于脑电图的个性化神经调节脑状态识别研究

2022 IEEE 15th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC) Pub Date : 2022-12-01 DOI:10.1109/MCSoC57363.2022.00053

Yu-Cheng Chang, Pin-Hsuan Chao, Sin-Horng Chen, Chun-Shu Wei

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引用次数: 0

摘要

重复经颅磁刺激(rTMS)是治疗难治性抑郁症(TRD)的一种非侵入性抗抑郁神经调节疗法。然而，患者的缓解率仍然不理想，这可能是由于传统rTMS方案的次优配置。本研究旨在设计一个闭环经颅磁刺激系统，验证基于脑电图实时监测的脑状态依赖性刺激的实用性。提出了一种新的相位估计方法，以提高脑电经颅磁刺激相触发的精度。我们的实现支持后续个性化脑状态依赖神经调节的临床应用研究。

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Toward EEG-Based Brain State Recognition for Personalized Neuromodulation

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive antidepressant neuromodulation therapy for treatment-resistant depression (TRD). However, the remission rate of patients remains unsatisfactory possibly due to the suboptimal configuration of conventional rTMS protocol. This work aims to design a close-loop TMS system and validate the practicability of brain-state-dependent stimulation based on real-time monitoring of electroencephalogram (EEG). We propose a novel method of phase estimation to enhance the precision of EEG phase-triggered firing of TMS. Our implementation supports subsequent studies on personalized brain-state-dependent neuromodulation for clinical applications.

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2022 IEEE 15th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)

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