Xie Xu, Wang Minmin, Zhang Shaomin
College of Biomedical Engineering & Instrument science, Zhejiang University, Hangzhou 310027, P. R. China.
Key Laboratory for Biomedical Engineering of Ministry of Education, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024 Aug 25;41(4):724-731. doi: 10.7507/1001-5515.202308016.
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.
经颅电刺激(TES)是一种具有巨大潜力的非侵入性神经调节技术。基于个体TES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,显著提高TES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天)的问题,并且存在诸如忽视刺激器输出通道数量受限等局限性,进一步阻碍了它们的临床应用。因此,本文提出了一种高效实用的电极优化方法。所提出的方法在限制所用电极数量的同时,对目标脑区内TES的强度和聚焦性进行同步优化,并且实现了更快的计算速度。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,显著减少了85.9%的计算时间。此外,我们的方法考虑了刺激器的可用通道数量,以便在多个电极之间分配电流,进一步提高了TES的耐受性。本文提出的电极优化方法具有高效且易于操作的特点,有可能为个体化TES的实施提供有价值的支持数据和参考。