A feature-based processing framework for real-time implementation of muscle fatigue measurement

2022 ◽  
Author(s):  
P. González-Zamora ◽  
Victor H. Benitez ◽  
Jesus Pacheco
2020 ◽  
Vol 65 (4) ◽  
pp. 461-468
Author(s):  
Jannatul Naeem ◽  
Nur Azah Hamzaid ◽  
Amelia Wong Azman ◽  
Manfred Bijak

AbstractFunctional electrical stimulation (FES) has been used to produce force-related activities on the paralyzed muscle among spinal cord injury (SCI) individuals. Early muscle fatigue is an issue in all FES applications. If not properly monitored, overstimulation can occur, which can lead to muscle damage. A real-time mechanomyography (MMG)-based FES system was implemented on the quadriceps muscles of three individuals with SCI to generate an isometric force on both legs. Three threshold drop levels of MMG-root mean square (MMG-RMS) feature (thr50, thr60, and thr70; representing 50%, 60%, and 70% drop from initial MMG-RMS values, respectively) were used to terminate the stimulation session. The mean stimulation time increased when the MMG-RMS drop threshold increased (thr50: 22.7 s, thr60: 25.7 s, and thr70: 27.3 s), indicating longer sessions when lower performance drop was allowed. Moreover, at thr70, the torque dropped below 50% from the initial value in 14 trials, more than at thr50 and thr60. This is a clear indication of muscle fatigue detection using the MMG-RMS value. The stimulation time at thr70 was significantly longer (p = 0.013) than that at thr50. The results demonstrated that a real-time MMG-based FES monitoring system has the potential to prevent the onset of critical muscle fatigue in individuals with SCI in prolonged FES sessions.


2021 ◽  
Vol 50 (2) ◽  
pp. 20200249-20200249
Author(s):  
贺文静 Wenjing He ◽  
胡坚 Jian Hu ◽  
陈育伟 Yuwei Chen ◽  
潘苗苗 Miaomiao Pan ◽  
朱运维 Yunwei Zhu ◽  
...  

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 89188-89204
Author(s):  
Junlu Wang ◽  
Chengfeng Liu ◽  
Linlin Ding ◽  
Hao Luo ◽  
Baoyan Song

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