Details

Autor(en) / Beteiligte

• Guo, Zhenhui
• Wang, Yue
• Zhang, Song
• Wu, Jinqiao
• Yu, Yang
• Dang, Yu
• Yu, Ningbo
• Wu, Jialing
• Han, Jianda

Titel

An sEMG-based Hill-type Model for Estimation of Swallowing Motion

Ist Teil von

• 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2021, p.790-794

Ort / Verlag

IEEE

Erscheinungsjahr

2021

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• Dysphagia is a common clinical symptom which can cause dehydration, malnutrition, pneumonia, and even death. Surface electromyography (sEMG) signals, which can be obtained in a non-invasive way, have been used for screening dysphagia, and estimation of the swallowing motion based on the sEMG signals is essential. In this paper, we propose an sEMG-based Hill-type model for estimation of swallowing motion. Firstly, the sEMG signals of suprahyoid and infrahyoid muscles and acceleration signals of larynx which represent the swallowing motion were collected simultaneously and preprocessed. Secondly, the relationship between the preprocessed sEMG signals and swallowing motion was established based on Hill-type muscle model and dynamics of larynx. Then experiments with four kinds of swallowing tasks were conducted to verify the proposed method. Analysis of the experimental results with normalized root-mean-square (NRMSE) and correlation coefficient (CC) verified the effectiveness of the proposed method.