Title :
A novel approach to localized muscle fatigue assessment
Author :
MacIsaac, D.T. ; Parker, P.A. ; Englehart, K.B.
Author_Institution :
Dept. of Electr. & Comput. Eng., New Brunswick Univ., Fredericton, NB, Canada
Abstract :
A method for generating a function which maps a set of surface myoelectric parameters to a fatigue index is proposed in this work. This forms the basis of a novel approach to assessing localized muscle fatigue with the myoelectric signal. An artificial neural network with a multilayer perceptron architecture was utilized to tune the function to emphasize trends in input parameters which are due to fatigue. The concept was tested empirically under static, cyclic, and random conditions. Results indicate improved performance when compared to fatigue assessment performance of mean frequency estimates.
Keywords :
biological techniques; biomechanics; electromyography; medical signal processing; multilayer perceptrons; artificial neural network; cyclic conditions; fatigue index; localized muscle fatigue assessment; mean frequency estimates; multilayer perceptron architecture; myoelectric signal; random conditions; static conditions; surface myoelectric parameters mapping; Artificial neural networks; Fatigue; Frequency estimation; Life estimation; Multilayer perceptrons; Muscles; Neural networks; Robustness; Signal mapping; Testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
Print_ISBN :
0-7803-7789-3
DOI :
10.1109/IEMBS.2003.1280420