Banga, B., Katashev, A., Greitāns, M.. Method for Muscle Fatigue Detection Using Inertial Sensors. In Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. 2023., 89(), 25-32 pp. Springer, 2023.
Bibtex citation:
Bibtex citation:
@inproceedings{15735_2023,
author = {Banga and B. and Katashev and A. and Greitāns and M.},
title = {Method for Muscle Fatigue Detection Using Inertial Sensors},
journal = {In Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. 2023.},
volume = {89},
pages = {25-32},
publisher = {Springer},
year = {2023}
}
author = {Banga and B. and Katashev and A. and Greitāns and M.},
title = {Method for Muscle Fatigue Detection Using Inertial Sensors},
journal = {In Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. 2023.},
volume = {89},
pages = {25-32},
publisher = {Springer},
year = {2023}
}
Abstract: 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.
Quartile: Q4