Title :
Segmentation of surface EMG signals
Author :
Sedlak, Jason ; Spulak, Daniel ; Cmejla, R. ; Bacakova, Radka ; Chrastkova, Martina ; Kracmar, Bronislav
Author_Institution :
Dept. of Circuit Theor., Czech Tech. Univ. in Prague, Prague, Czech Republic
Abstract :
This paper compares two different approaches to electromyographic (EMG) segmentation for the purpose of muscle activation pattern identification. A widely known linear EMG envelope technique is compared with a newly designed method based on marker detection in a video. The results are evaluated by comparison of the muscle activity intervals. The experiments show that the video-based technique can achieve similar results to the EMG envelope. The EMG segmentation based on the video processing is more robust for segmentation of various types of EMG signal.
Keywords :
electromyography; medical signal detection; medical signal processing; pattern classification; electromyography; linear EMG envelope technique; marker detection; muscle activation pattern identification; muscle activity; surface EMG signal segmentation; video processing; video-based technique; Databases; Educational institutions; Electromyography; Muscles; Signal processing algorithms; Surface treatment; Video recording; EMG segmentation; digital signal processing; electromyography; kinesiology; muscle onset detection;
Conference_Titel :
Applied Electronics (AE), 2013 International Conference on
Conference_Location :
Pilsen
Print_ISBN :
978-80-261-0166-6