@inproceedings{0df29cc7643c4b8f95b05bb49434833c,
title = "Muscle Tension Analysis Based on sEMG Signal with Wearable Pulse Diagnosis Device",
abstract = "Traditional Chinese medicine (TCM) is an empirical and subjective medical discipline. The rapid development of information technology requires the objectification of traditional Chinese medicine diagnosis and treatment. A wearable pulse diagnosis device, which aims at making pulse diagnosis objective, is designed. The device utilizes 7 kind of signals to characterize human health level. This paper especially focuses on the application of sEMG signal in the analysis of muscle tension and classifies muscle tension level using the algorithm of CART. In actual wearing cases, different wearing positions will induce to big difference of sEMG signal. In order to solve the problem above, random forest is applied in a position matching method based on prior calibration. The experimental results prove the effectiveness of the muscle tension level classification algorithm with an accuracy up to 81.4%.",
keywords = "Pulse diagnosis, Random forest, Wearable device, sEMG",
author = "Xin Chang and Xinyi Li and Jian Li and Guihua Tian and Hongcai Shang and Jingbo Hu and Jiahao Shi and Yue Lin",
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 = "10.1007/978-3-030-89092-6_69",
language = "English",
isbn = "9783030890919",
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 = "756--766",
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 = "Germany",
}
