基于连续小波变换的面肌电信号解码奇异检测

Yuxuan Zhou, Xiaoying Lu, Zhigong Wang, Zonghao Huang, Jingdong Yang, Xintai Zhao
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引用次数: 3

摘要

肌电图(EMG)信号是肌肉收缩过程中肌纤维电活动的结果,其模式可以为运动康复系统提供重要参考。采用“不应期”和“阈值”的肌电解码方法算法复杂度低,时域信息保真度好,适用于实时处理系统。本文分析了连续小波变换模极大值之间的间隔分布,为“不应期”的合理确定提供了依据。此外,根据“不应期”对源信号进行解码。结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Surface myoelectric signals decoding using the continuous wavelet transform singularity detection
Electromyographic (EMG) signals are the resultant of electrical activity of muscle fibers during a muscle contraction, whose pattern can provide a significant reference of a motor rehabilitation system. The EMG decoding method using “refractory period” and “threshold” is appropriate for real-time processing system due to its low algorithm complexity and the good fidelity of time domain information. In this paper, the distribution of intervals between continuous wavelet transform modulus maxima was analyzed to provide a reasonable determination of the “refractory period”. In addition, the source signals were decoded according to the “refractory period”. Promising results are demonstrated.
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