Title :
Research of Feature Extraction Method for Stroke Patients´ Surface Electromyography
Author :
Liye, Ren ; Xiaoli, Wang ; Xiao, Wang
Author_Institution :
Dept. of Electron. Inf. Eng., Changchun Univ., Changchun, China
Abstract :
Surface electromyography is a one-dimensional time series signal of neuromuscular system recorded from skin surface. It can reflect the states of muscle activity and muscle function accurately. All the subjects had to perform dynamic contraction for stroke´s knee flexion and extension in experiment. The surface electromyography were collected by surface electrodes and then processed by linear time and frequency-domain method. SEMG characteristics extraction has been done and an eigenvector space of mode recognition was built, and lies the theoretical and technical foundation for stroke patients´ rehabilitation training.
Keywords :
electromyography; feature extraction; frequency-domain analysis; medical signal processing; patient rehabilitation; SEMG characteristics extraction; dynamic contraction; eigenvector space; feature extraction method; frequency-domain method; linear time method; mode recognition; muscle activity; muscle function; neuromuscular system; one-dimensional time series signal; skin surface; stroke knee flexion; stroke patient rehabilitation training; stroke patient surface electromyography; surface electrode; Eigenvalues and eigenfunctions; Electrodes; Electromyography; Frequency domain analysis; Muscles; Skin; Time domain analysis; feature extraction; storke; surface electromyography;
Conference_Titel :
Intelligent Networks and Intelligent Systems (ICINIS), 2012 Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4673-3083-1
DOI :
10.1109/ICINIS.2012.78
