[An efficient and practical electrode optimization method for transcranial electrical stimulation].

Q4 Medicine
Xu Xie, Minmin Wang, Shaomin Zhang
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引用次数: 0

Abstract

Transcranial electrical stimulation (TES) is a non-invasive neuromodulation technique with great potential. Electrode optimization methods based on simulation models of individual TES field could provide personalized stimulation parameters according to individual variations in head tissue structure, significantly enhancing the stimulation accuracy of TES. However, the existing electrode optimization methods suffer from prolonged computation times (typically exceeding 1 d) and limitations such as disregarding the restricted number of output channels from the stimulator, further impeding their clinical applicability. Hence, this paper proposes an efficient and practical electrode optimization method. The proposed method simultaneously optimizes both the intensity and focality of TES within the target brain area while constraining the number of electrodes used, and it achieves faster computational speed. Compared to commonly used electrode optimization methods, the proposed method significantly reduces computation time by 85.9% while maintaining optimization effectiveness. Moreover, our method considered the number of available channels for the stimulator to distribute the current across multiple electrodes, further improving the tolerability of TES. The electrode optimization method proposed in this paper has the characteristics of high efficiency and easy operation, potentially providing valuable supporting data and references for the implementation of individualized TES.

[高效实用的经颅电刺激电极优化方法]。
经颅电刺激(TES)是一种潜力巨大的非侵入性神经调控技术。基于个体经颅电刺激场模拟模型的电极优化方法可根据头部组织结构的个体差异提供个性化刺激参数,从而显著提高经颅电刺激的刺激精度。然而,现有的电极优化方法存在计算时间长(通常超过 1 d)、不考虑刺激器输出通道数量限制等局限性,进一步阻碍了其临床应用。因此,本文提出了一种高效实用的电极优化方法。该方法在限制电极使用数量的同时,还能优化目标脑区的 TES 强度和聚焦度,而且计算速度更快。与常用的电极优化方法相比,所提出的方法在保持优化效果的同时,大大减少了 85.9% 的计算时间。此外,我们的方法还考虑了刺激器的可用通道数量,以在多个电极上分配电流,从而进一步提高了 TES 的耐受性。本文提出的电极优化方法具有效率高、操作简便等特点,可为个体化 TES 的实施提供有价值的支持数据和参考。
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
生物医学工程学杂志
生物医学工程学杂志 Medicine-Medicine (all)
CiteScore
0.80
自引率
0.00%
发文量
4868
期刊介绍:
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