中文版 | English
题名

基于柔性电极材料的高密度肌电获取与肌群协同分析

其他题名
HIGH DENSITY EMG ACQUISITION AND MUSCLE SYNERGY ANALYSIS BASED ON FLEXIBLE ELECTRODE MATERIALS
姓名
姓名拼音
CHEN Ziyin
学号
12132506
学位类型
硕士
学位专业
0856 材料与化工
学科门类/专业学位类别
0856 材料与化工
导师
耿艳娟
导师单位
深圳理工大学(筹)
论文答辩日期
2023-05-15
论文提交日期
2023-07-06
学位授予单位
南方科技大学
学位授予地点
深圳
摘要

脑卒中和脑外伤等神经损伤性疾病是造成患者运动功能障碍的主要原 因。临床康复训练的一个关键问题是如何对患者的神经肌肉功能进行科学、 量化地评价,以阐明康复训练效果及神经康复机制。肌群协同是运动功能 评估的重要手段。然而,肌群协同相关研究存在两个问题:第一,目前常 用的电极质地较硬,难以与人体皮肤表面紧密贴合,导致所采集的数据质 量不佳。第二,传统的肌群协同分析方法局限于少通道且分布在大肌肉, 无法对人体前臂等小肌肉部位的肌群协同进行客观分析。针对这些问题, 本研究开展了两个主要工作:第一,为获取高质量的表面肌电信号,研究 柔性材料电极的制备和高密度肌电的采集方法;第二,为了研究等长、等 张运动模式下腕部动作的肌群协同特性,提出基于高密度肌电的肌群协同 分析方法。 本研究研究了一种柔性材料电极的制备方法。在电极制备过程中,本 研究把基底材料固定好后放入磁控溅射镀膜机,调整好所需要的溅射气压 与溅射功率,再向基底材料表面溅射 10 秒的金,通过磁控溅射的方法制 备所需的柔性可拉伸材料电极。在肌电采集过程中,本研究将制备好的柔 性材料电极粘贴在被试者前臂肌肉皮肤表面,将电极的接口端与 TMSI 高 密度肌电采集系统相连,采集到了信噪比高、特征明显的高密度表面肌电 信号。 本研究使用非负矩阵分解法从高密度肌电中提取肌群协同并对其特性 进行分析。采用了夹角余弦和欧式距离来度量肌群协同之间的相似程度, 并用判别分析法对同种运动模式内的激活系数进行分类识别。此外,本研 究采用 K-Means 聚类法来寻找每种运动模式下的具有代表性的肌群协同, 定义夹角余弦大于或等于 0.85 的协同向量为共有协同向量。结果表明,同 种运动模式内肌群协同相似度高。两种运动模式间的肌群协同相似度降低。 同种运动模式下不同条件下的激活系数明显不同。不同运动模式之间存在 共有协同向量。本研究为临床运动功能评估提供了基于高密度肌电的肌群 协同分析方法,为临床康复训练提供指导意义。

关键词
语种
中文
培养类别
独立培养
入学年份
2021
学位授予年份
2023-06
参考文献列表

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所在学位评定分委会
材料与化工
国内图书分类号
TM930
来源库
人工提交
成果类型学位论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/545180
专题中国科学院深圳理工大学(筹)联合培养
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GB/T 7714
陈子寅. 基于柔性电极材料的高密度肌电获取与肌群协同分析[D]. 深圳. 南方科技大学,2023.
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