An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy
Muscle activity is composed of fast and slow activations. The detection of the onset time of the electromyogram signal, which is slowly activated, is difficult. This paper proposes a detection method based on marginal spectral entropy (MSE). The surface electromyography (sEMG) signal of the soleus d...
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MDPI AG
2025-05-01
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| Online Access: | https://www.mdpi.com/1424-8220/25/10/2963 |
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| author | Xiaolei Huang Jinzhuang Xiao Qing Chang Bin Fang |
| author_facet | Xiaolei Huang Jinzhuang Xiao Qing Chang Bin Fang |
| author_sort | Xiaolei Huang |
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| description | Muscle activity is composed of fast and slow activations. The detection of the onset time of the electromyogram signal, which is slowly activated, is difficult. This paper proposes a detection method based on marginal spectral entropy (MSE). The surface electromyography (sEMG) signal of the soleus during normal walking was collected by a wireless electromyography acquisition system. The proposed MSE-based detection method is based on the Hilbert–Huang transform (HHT) combined with information entropy. By comparing the changes in MSE before and after muscle activation to plot a trend line, the point of fastest change on the trend line was defined as the onset time of muscle activation. This method was compared with the amplitude threshold method and the Teager–Kaiser energy (TKE) operator method. The results show that the onset time of muscle activation detected by this method is 0.14 s earlier than the amplitude threshold method and 0.16 s earlier than the TKE operator method. The detection results were significantly different (<i>p</i> < 0.05), indicating that this method has higher detection accuracy for the onset time of the sEMG signal, which is slowly activated. |
| format | Article |
| id | doaj-art-b5641175d79f44e4bb770f3db89c4471 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-b5641175d79f44e4bb770f3db89c44712025-08-20T01:56:39ZengMDPI AGSensors1424-82202025-05-012510296310.3390/s25102963An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum EntropyXiaolei Huang0Jinzhuang Xiao1Qing Chang2Bin Fang3College of Electrical Engineering, Hebei University of Architecture, Zhangjiakou 075000, ChinaCollege of Eletronic and Information Engineering, Hebei University, Baoding 071000, ChinaCollege of Electrical Engineering, Hebei University of Architecture, Zhangjiakou 075000, ChinaCollege of Electrical Engineering, Hebei University of Architecture, Zhangjiakou 075000, ChinaMuscle activity is composed of fast and slow activations. The detection of the onset time of the electromyogram signal, which is slowly activated, is difficult. This paper proposes a detection method based on marginal spectral entropy (MSE). The surface electromyography (sEMG) signal of the soleus during normal walking was collected by a wireless electromyography acquisition system. The proposed MSE-based detection method is based on the Hilbert–Huang transform (HHT) combined with information entropy. By comparing the changes in MSE before and after muscle activation to plot a trend line, the point of fastest change on the trend line was defined as the onset time of muscle activation. This method was compared with the amplitude threshold method and the Teager–Kaiser energy (TKE) operator method. The results show that the onset time of muscle activation detected by this method is 0.14 s earlier than the amplitude threshold method and 0.16 s earlier than the TKE operator method. The detection results were significantly different (<i>p</i> < 0.05), indicating that this method has higher detection accuracy for the onset time of the sEMG signal, which is slowly activated.https://www.mdpi.com/1424-8220/25/10/2963muscle activationslow activationHilbert–Huang transform (HHT)marginal spectrum entropy (MSE) |
| spellingShingle | Xiaolei Huang Jinzhuang Xiao Qing Chang Bin Fang An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy Sensors muscle activation slow activation Hilbert–Huang transform (HHT) marginal spectrum entropy (MSE) |
| title | An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy |
| title_full | An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy |
| title_fullStr | An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy |
| title_full_unstemmed | An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy |
| title_short | An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy |
| title_sort | onset detection method for slowly activated muscle based on marginal spectrum entropy |
| topic | muscle activation slow activation Hilbert–Huang transform (HHT) marginal spectrum entropy (MSE) |
| url | https://www.mdpi.com/1424-8220/25/10/2963 |
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