A Real-Time Artifact Removal System for Closed-Loop Deep-Brain Stimulation

IF 5.2 2区医学 Q2 ENGINEERING, BIOMEDICAL

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2025-08-15 DOI:10.1109/TNSRE.2025.3597916

Chenghao Xing;Xi Cheng;Hao Feng;Bin Wu;Yingnan Nie;Chunguang Chu;Xin Zhang;Qiyu Niu;Jia Xiu;Bowen Geng;Liang Chen;Shouyan Wang

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引用次数: 0

Abstract

This paper presents a novel real-time signal processing method for removing local field potential (LFP) artifacts during deep-brain stimulation (DBS). Real-time artifact removal is essential for closed-loop DBS systems, as they rely on real-time, artifact-free LFPs to provide stimulation feedback. Building on previous stimulation-sampling synchronization methods, this work introduces a dynamic template subtraction method that achieves precise and efficient real-time removal of stimulation artifacts. By leveraging stimulation-sampling synchronization, the method enables real-time template alignment and artifact removal through subtraction. It can operate even at low sampling rates, requiring a minimum of twice the stimulation frequency. The artifact templates are dynamically updated to adapt to changes in stimulation artifacts, ensuring robust and accurate performance over time. The method was evaluated through simulations and in vitro and in vivo experiments. Simulation tests validated its theoretical feasibility, while it successfully removed stimulation artifacts in vitro, relative errors in the power spectral density between the recovered and reference LFPs in the examined frequency band (1—150 Hz) were 0.64%, 0.31%, 0.58%, and 0.73% under stimulation at 20, 60, 90, and 130 Hz, respectively. In vivo, the method successfully recorded artifact-free LFPs in real time and supported beta-triggered closed-loop DBS. In an additional in vivo evaluation using a commercial medical device, the method recorded artifact-free LFPs with a sampling rate of 260 Hz (twice the stimulation frequency of 130 Hz). The proposed artifact removal method provides important technical support for realizing lightweight closed-loop DBS systems.

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一种用于闭环深部脑刺激的实时伪影去除系统。

提出了一种消除脑深部刺激（DBS）过程中局部场电位（LFP）伪影的实时信号处理方法。实时伪影去除对于闭环DBS系统至关重要，因为它们依赖于实时、无伪影的lfp来提供刺激反馈。在之前的刺激采样同步方法的基础上，本研究引入了一种动态模板减法，实现了精确、高效的实时去除刺激伪影。通过利用刺激采样同步，该方法可以通过减法实现实时模板对齐和伪影去除。它甚至可以在低采样率下工作，至少需要两倍的刺激频率。工件模板可以动态更新，以适应刺激工件的变化，确保随着时间的推移实现稳健和准确的性能。通过模拟实验和体外、体内实验对该方法进行了评价。仿真测试验证了该方法的理论可行性，同时成功地消除了体外刺激伪影，在20、60、90和130 Hz的刺激下，在检测频段（1-150 Hz）内，恢复的LFPs与参考LFPs之间的功率谱密度相对误差分别为0.64%、0.31%、0.58%和0.73%。在体内，该方法成功地实时记录了无伪影的lfp，并支持β触发的闭环DBS。在使用商业医疗设备进行的另一项体内评估中，该方法记录了采样率为260 Hz（刺激频率为130 Hz的两倍）的无伪影lfp。所提出的伪影去除方法为实现轻量化闭环DBS系统提供了重要的技术支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Neural Systems and Rehabilitation Engineering 医学-工程：生物医学

CiteScore

8.60

自引率

8.20%

发文量

479

审稿时长

6-12 weeks

期刊介绍： Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.