Title :
A Novel Electromyography Simulator Based on Experiment Data
Author :
Xingwei Li ; Wei Li
Author_Institution :
Dept. of Autom. Control, Nat. Univ. of Defense Technol., Changsha, China
Abstract :
As the development of those Electromyography assisted biodynamic models, the requirements of Electromyography (EMG) signals have become increasingly important. Traditionally, subjects always need whenever experiment need to put into practice. Therefore, the requirements of EMG simulation increased significantly. The traditional method for the simulation of EMG is based on the physiological mechanisms of muscle contraction. So, it is very important to deeply understand the physiological mechanisms of muscle contraction. Actually, this mechanism is very complicated, and it is usually very hard to simulation the specific EMG signals for a specific subject. A new technique was developed. It is based on the experiment data and eliminates the need to collect EMG signals by electrode. This new technique demonstrated at least as similar signal shapes and similar model fidelity when compared to the traditional technique, indicating that it is a valid alternative to traditional method. The subjects who were once joined the experiment and the EMG collection systems are no longer needed. In particular, this technique will be valuable for evaluating some exertion once can´t be taken, or can´t be finished by the specific subject. In addition, based on those already existing subjects, it is very easy to set the relevant properties of specific subject, and then generate virtual subject and the simulated EMG signal according to any simulation conditions.
Keywords :
biomechanics; electromyography; feature extraction; medical signal processing; pattern matching; physiological models; signal reconstruction; virtual reality; EMG signal collection system; EMG signal simulation requirement; electromyography assisted biodynamic model development; electromyography simulator; experiment data; muscle contraction mechanism; physiological mechanism; similar model fidelity; similar signal shape; simulation condition; specific subject properties; virtual subject generation; Biological system modeling; Data models; Databases; Electromyography; Muscles; Neural networks; Physiology; Biomechanical model; Electromyography (EMG); Experiment data; Lifting; Simulator; Subject;
Conference_Titel :
Instrumentation and Measurement, Computer, Communication and Control (IMCCC), 2014 Fourth International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-6574-8
DOI :
10.1109/IMCCC.2014.26