@inproceedings{8f3059b0afe5458d9595d1a89e7ec9f9,
title = "Robustness of Combined sEMG and Ultrasound Modalities Against Muscle Fatigue in Force Estimation",
abstract = "It is evident that surface electromyography (sEMG) based prosthesis is constrained due to sensitivity to muscle fatigue. This paper investigated the muscle fatigue robustness for sEMG, ultrasound and the fusion sEMG/ultrasound signals towards the proportional force prediction. The linear regression model is developed, and evaluated on the non-fatigue state and fatigue state. Seven able-bodied subjects participated in the experiment to validate the model. The results demonstrate that sEMG outperforms ultrasound in force estimation accuracy, but ultrasound is more robust against muscle fatigue than sEMG. Furthermore, the fusion sEMG/ultrasound signal shows comparable force prediction accuracy to sEMG and better muscle fatigue robustness than sEMG. The fusion sEMG/ultrasound modality overcomes the defect of sEMG modality, making it a promising modality for the long-term use of prosthetic force control.",
keywords = "A-mode ultrasound, Force estimation, Muscle fatigue, sEMG",
author = "Jia Zeng and Yu Zhou and Yicheng Yang and Zenglin Xu and Hongwei Zhang and Honghai Liu",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 14th International Conference on Intelligent Robotics and Applications, ICIRA 2021 ; Conference date: 22-10-2021 Through 25-10-2021",
year = "2021",
doi = "10.1007/978-3-030-89134-3\_20",
language = "英语",
isbn = "9783030891336",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "213--221",
editor = "Xin-Jun Liu and Zhenguo Nie and Jingjun Yu and Fugui Xie and Rui Song",
booktitle = "Intelligent Robotics and Applications - 14th International Conference, ICIRA 2021, Proceedings",
address = "德国",
}