神经电极阵列植入脑组织的力学行为分析。

IF 3 3区 工程技术 Q2 CHEMISTRY, ANALYTICAL
Micromachines Pub Date : 2025-08-31 DOI:10.3390/mi16091010
Xinyue Tan, Bei Tong, Kunyang Zhang, Changmao Ni, Dengfei Yang, Zhaolong Gao, Yuzhao Huang, Na Yao, Li Huang
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引用次数: 0

摘要

了解植入神经电极阵列的力学行为对脑机接口的发展至关重要,是确保手术安全性、植入精度、评估电极疗效和长期稳定性的基础。因此,一个可靠的有限元模型可以有效地减少动物实验,并且对于更深入地了解植入过程的机制至关重要。本研究建立了一种新的模拟神经电极植入脑组织的有限元模型,具体表征了脑组织的非线性力学响应。采用离体猪脑组织进行同步电极植入实验。结果表明,该模型准确地再现了电极植入过程的动力学过程。定量分析表明,植入力与插入深度呈正相关,多电极阵列中每个电极的平均植入力随着电极数量的增加而降低,电极尺寸、杆间距和插入速度的提高都有助于插入力的系统性增加。本研究为高密度神经电极阵列的植入力预测提供了可靠的仿真工具和深入的机理分析,为BCI植入装置的优化设计提供了理论指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mechanical Behavior Analysis of Neural Electrode Arrays Implantation in Brain Tissue.

Understanding the mechanical behavior of implanted neural electrode arrays is crucial for BCI development, which is the foundation for ensuring surgical safety, implantation precision, and evaluating electrode efficacy and long-term stability. Therefore, a reliable FE models are effective in reducing animal experiments and are essential for a deeper understanding of the mechanics of the implantation process. This study established a novel finite element model to simulate neural electrode implantation into brain tissue, specifically characterizing the nonlinear mechanical responses of brain tissue. Synchronized electrode implantation experiments were conducted using ex vivo porcine brain tissue. The results demonstrate that the model accurately reproduces the dynamics of the electrode implantation process. Quantitative analysis reveals that the implantation force exhibits a positive correlation with insertion depth, the average implantation force per electrode within a multi-electrode array decreases with increasing electrode number, and elevation in electrode size, shank spacing, and insertion speed each contribute to a systematic increase in insertion force. This study provides a reliable simulation tool and in-depth mechanistic analysis for predicting the implantation forces of high-density neural electrode arrays and offer theoretical guidance for optimizing BCI implantation device design.

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来源期刊
Micromachines
Micromachines NANOSCIENCE & NANOTECHNOLOGY-INSTRUMENTS & INSTRUMENTATION
CiteScore
5.20
自引率
14.70%
发文量
1862
审稿时长
16.31 days
期刊介绍: Micromachines (ISSN 2072-666X) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to micro-scaled machines and micromachinery. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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