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Event Detection of Muscle Activation Using an Electromyogram
Applied Sciences ( IF 2.838 ) Pub Date : 2020-08-12 , DOI: 10.3390/app10165593
Kimoon Kang , Kiwon Rhee , Hyun-Chool Shin

In this study, we proposed a precise onset and offset detection algorithm for muscle activation by using an electromyogram (EMG). The adaptive threshold was determined using the constant false alarm rate algorithm. The EMG signal was refined by morphological hole filling, which is used to close up and fill out missing information. By exploiting the EMG amplitude ratio in two channels, we significantly improved the offset detection performance. The proposed method does not require a training process, unlike conventional methods. The experimental results indicated that the estimated errors for both the onset and offset detection are lower than those obtained using two of the conventional methods.

中文翻译:

使用肌电图检测肌肉激活的事件

在这项研究中,我们提出了一种通过使用肌电图(EMG)进行肌肉激活的精确的起始和偏移检测算法。使用恒定误报率算法确定自适应阈值。EMG信号通过形态学填充填补,用于封闭和填充缺失信息。通过利用两个通道的EMG振幅比,我们显着提高了偏移检测性能。与常规方法不同,所提出的方法不需要训练过程。实验结果表明,用于开始和偏移检测的估计误差均低于使用两种常规方法获得的误差。
更新日期:2020-08-12
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