Method for Muscle Fatigue Detection Using Inertial Sensors

惯性测量装置 肱二头肌 肌肉疲劳 肌电图 物理医学与康复 前臂 肘关节屈曲 惯性参考系 康复 肘部 医学 计算机科学 物理疗法 人工智能 解剖 物理 量子力学
作者
Beāte Banga,Alexei Katashev,Modris Greitāns
出处
期刊:IFMBE proceedings [Springer Nature]
卷期号:: 25-32 被引量:1
标识
DOI:10.1007/978-3-031-37132-5_4
摘要

Muscle fatigue is a common symptom that many people experience and is associated with difficulties in voluntary movement, which can lead to injuries. Currently, surface electromyography (sEMG) is considered the gold standard for muscle fatigue estimation, but its accuracy can be impacted by various factors. Therefore, new methods, such as the use of inertial sensors (IMU), are being introduced. This study aimed to explore the relationship between muscle fatigue and biomechanical parameters using inertial sensors and sEMG as a validation tool. Four participants performed an elbow flexion exercise, and the data from IMU sensor nodes and sEMG were collected. The results showed that there were correlations between the electrical activity of m. biceps brachii and rotation angles of the forearm and upper arm. Additionally, an increase in motion amplitude deviation was found to be a potential indicator of muscle fatigue. These findings suggest that inertial sensors can be used as an alternative to sEMG for detecting muscle fatigue, which has potential implications for injury prevention and rehabilitation. However, further research with a larger sample size is needed to validate these findings.
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