Title :
Alterations in the Peak Amplitude Distribution of the Surface Electromyogram Poststroke
Author :
Xiaoyan Li ; Suresh, A. ; Ping Zhou ; Rymer, William Z.
Author_Institution :
Sensory Motor Performance Program, Rehabilitation Inst. of Chicago, Chicago, IL, USA
Abstract :
We introduce a new method to examine the spinal motoneuron involvement after stroke using a surface electromyography (EMG) recording system. Fourteen chronic stroke survivors with mild to severe muscle weakness participated in the study. Surface EMG signals were collected from the first dorsal interosseous muscle while subjects performed isometric index finger abduction with paretic or contralateral hand at different matched force levels. Compared with the contralateral muscles, different patterns of peak amplitude distribution were observed at the paretic muscles, which could be induced by motor unit pathological alterations following a stroke. Compared with the conventional electrophysiological methods, the peak amplitude distribution analysis proposed in this study provides a convenient approach to help identify specific mechanisms of muscle weakness and other symptoms after stroke.
Keywords :
brain; electromyography; medical disorders; medical signal processing; neurophysiology; chronic stroke survivors; contralateral hand; conventional electrophysiological methods; dorsal interosseous muscle; isometric index finger abduction; matched force levels; mild muscle weakness; motor unit pathological alterations; paretic muscle weakness; peak amplitude distribution; peak amplitude distribution alterations; severe muscle weakness; spinal motoneuron involvement; stroke symptoms; surface EMG signal collection; surface electromyogram post-stroke; surface electromyography recording system; Electromyography; Fingers; Force; Gaussian distribution; Indexes; Muscles; Optical fiber sensors; Amplitude distribution; peak detection; stroke; surface electromyography (EMG); Adult; Aged; Analysis of Variance; Electrodes; Electromyography; Female; Fingers; Humans; Male; Middle Aged; Muscle, Skeletal; Signal Processing, Computer-Assisted; Stroke;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2012.2205249