开发高速度肌肉活动监测器的优化策略,使用多分辨率的能量操作员.
Shenglin Wang1, Guosheng Zhao1, Yiwei Liao1
1College of Computer Science and Information Engineering, Harbin Normal University, Harbin, China.
Frontiers in bioengineering and biotechnology
|April 16, 2025
概括
使用多分辨率能量运算符 (MTEO) 的新方法改善了电肌图 (EMG) 信号活动检测. 这种方法提高了 EMG 分析在各个领域的准确性和效率.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 人与机器的互动 人与机器的互动
背景情况:
- 电肌图 (EMG) 信号分析对于医学诊断,体育科学和人机交互至关重要.
- 目前的研究优先考虑EMG信号识别,而不是精确的起点/偏移检测.
- 在EMG信号中准确检测肌肉活动变化点需要进一步调查.
研究的目的:
- 引入一种新的方法来检测EMG信号活动,使用Teager-Kaiser能量运算器 (TKEO) 的变体.
- 开发和评估基于多分辨率能源运营商 (MTEO) 的两个EMG活动检测策略.
主要方法:
- 提出了多分辨率能源运营商 (MTEO) 作为EMG信号活动检测的新方法.
- 使用MTEO开发了一个基于值的探测器 (MEOTD) 和一个卷积神经网络模拟探测器 (MEONND).
- 采用分析层次过程 (AHP) 在真实EMG数据上对探测器性能进行半主观评估.
主要成果:
- 该MTEO展示了EMG信号的卓越预处理能力.
- 基于MTEO的探测器 (MEOTD和MEONND) 显示出更高的可靠性和准确性.
- MEONND实现了计算效率和高精度的平衡.
结论:
- 提出的基于MTEO的方法可以提高EMG信号活动检测质量和效率,而不会增加算法复杂性.
- 这种技术为各种应用提供了有价值的工具,包括人体工程学,人机交互和生物医学工程.
- 该研究强调了MTEO在推进EMG信号分析方面的潜力.
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