شماره ركورد كنفرانس :
4418
عنوان مقاله :
Nonlinear Analysis of Surface EMG Signal to Assess Muscle Fatigue during Isometric Contraction
پديدآورندگان :
Biyouki Fariba Dept. of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Iran , Rahati Saeed Dept. of Electrical Engineering, Mashhad Branch, Islamic Azad University, Iran , Laimi Katri Dept. of Physical Medicine and Rehabilitation, Turku University Hospital, Turku, Finland , Shoeibi Ali Assistant Professor of Neurology, Mashhad University of Medical Sciences, Iran
كليدواژه :
Biceps brachii muscle , correlation dimension , higher order statistics , surface electromyographic signal , muscle fatigue
عنوان كنفرانس :
يازدهمين كنفرانس سراسري سيستم هاي هوشمند
چكيده فارسي :
The objective of the present study was to investigate the possible relationship between nonlinear parameters extracted from surface EMG (sEMG) signals and muscle force and fatigue. Our hypothesis was that changes in motor unit recruitment during muscle contraction and fatigue, affect sEMG distribution and the intractions in muscle. Thus, five features based on geometric aspects of time series trajectory and higher order statistics were extracted from sEMG signal, recorded from biceps brachii muscle of a healthy female volunteer during rest, sustained (fatiguing) 50% MVC, 100% MVC and recovery. Results obtained from correlation dimension (CD) and linearity test (sl) analyses showed that the values of these parameters are higher during rest and recovery states, indicating higher chaotic behaviour, while they decreased during MVCs. However, when fatigue occurred, these parameters increased slightly, again. On the other hand, test of non-Gaussianity based on negentropy showed the reverse pattern of CD and sl. Skweness and kurtosis values, which are the quantitative descriptors of probability densities, were positive and negative, respectively during rest and recovery, while this pattern reversed for MVCs
