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Updated: Jun 9, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
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Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

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403

[基于肌肉疲劳特征的实时融合的基于表面电动图的手势识别的增强算法]

Shijia Yan1,2, Ye Yang1,2, Peng Yi1,2

  • 1College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, P. R. China.

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
|October 27, 2024
PubMed
概括

这项研究引入了一个实时算法,通过结合肌肉疲劳特征来改进基于表面肌电图的手势识别. 该方法提高了手势识别在各种疲劳水平和受试者的准确性.

关键词:
卷积神经网络是一种卷积神经网络.手的手势识别手势识别长期短期记忆 长期短期记忆肌肉疲劳导致肌肉疲劳.表面电动图表表的表面电动图.

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Wave summation
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