Related Experiment Video
Updated: Jun 10, 2026

Extraction of the EPP Component from the Surface EMG
Published on: December 16, 2009
[Phase space reconstruction of mastication muscles surface electromyography signal based on nonlinear dynamics]
Bo Zou1, Xiao-bo Wu, Shan-dan He
1Department of Prosthodontics, Guanghua School and Hospital of Stomatology & Institute of Stomatological Research, Sun Yat-sen University, Guangzhou 510055, China. tsoubocn@hotmail.com
Objective:
To calculate the delay times and embedding dimensions of surface electromyogragh (sEMG) signal of the masseter and temporal muscle during clenching at intercuspal position (ICP), and to reconstruct the space phase of sEMG signal with method of nonlinear dynamics.
Methods:
Ten male and 10 female young volunteers with normal masticatory system were included in the study, the signals of surface sEMG of bilateral masseter and temporal muscles in the position of ICP were collected, and the delay times and embedding dimensions of the sEMG signals were calculated using C-C method, the space phase of the sEMG signals was reconstructed.
Results:
A program of nonlinear dynamic analysis of mastication muscles sEMG signals was developed base on the platform of Matlab. The signals of the sEMG of the masseters and temporals were analyzed with nonlinear dynamic methods, the delay times and embedding dimensions of each muscles sEMG signals were obtained, and the space phase of each sEMG signals were reconstructed. The graphs of the space phase indicated the typical characteristic of chaotic attractor.
Conclusions:
The signals of the masseter and temporal muscles of surface sEMG during clenching at ICP of normal masticatory system show the typical characters of chaos, the methods of nonlinear dynamics are effective to analyze the sEMG signals of mastication system.
More Related Videos
08:09Multifunctional Setup for Studying Human Motor Control Using Transcranial Magnetic Stimulation, Electromyography, Motion Capture, and Virtual Reality
Published on: September 3, 2015
09:42Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
Published on: January 24, 2025