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Photonic Network Communications
Erschienen in: Photonic Network Communications 2/2019

19.11.2018 | Original Paper

Research on EMG segmentation algorithm and walking analysis based on signal envelope and integral electrical signal

verfasst von: Mo Wang, Xin’an Wang, Chen Peng, Sixu Zhang, Zhuochen Fan, Zhong Liu

Erschienen in: Photonic Network Communications | Ausgabe 2/2019

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Abstract

Surface electromyography (SEMG) is an important tool for analyzing gait movements. Effective segmentation of electromyography (EMG) start/end points is an important step in the analysis of EMG signals. This paper presents a SEMG segmentation algorithm based on signal envelope and integral electromyography. Compared with manual segmentation, the coincidence rate is more than 90%. There is no statistical difference in the characteristic parameters of EMG signals calculated from the start/end points obtained by the segmentation algorithm and the manual segmentation method (P > 0.05). Based on this segmentation algorithm, quantitative analysis and comparison of the force situation of the iliopsoas, musculus gracilis, soleus and tibialis anterior muscles during the complete gait cycle are performed. This study lays the foundation for the application of surface electromyography in the field of rehabilitation analysis and control, such as rehabilitation training and rehabilitation robots.
Vorheriger Artikel On the information transmission delay of the lexicographic product of digraphs
Nächster Artikel Design and analysis of an ID-updated mutual authentication protocol for mobile RFID system

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Metadaten
Titel
Research on EMG segmentation algorithm and walking analysis based on signal envelope and integral electrical signal
verfasst von
Mo Wang
Xin’an Wang
Chen Peng
Sixu Zhang
Zhuochen Fan
Zhong Liu
Publikationsdatum
19.11.2018
Verlag
Springer US
Erschienen in
Photonic Network Communications / Ausgabe 2/2019
Print ISSN: 1387-974X
Elektronische ISSN: 1572-8188
DOI
https://doi.org/10.1007/s11107-018-0809-1

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