A novel approach to localized muscle fatigue assessment

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.

[1]  R.N. Scott,et al.  A new strategy for multifunction myoelectric control , 1993, IEEE Transactions on Biomedical Engineering.

[2]  J. Suri Two-dimensional fast magnetic resonance brain segmentation , 2001, IEEE Engineering in Medicine and Biology Magazine.

[3]  Paolo Bonato,et al.  Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions , 2001, IEEE Transactions on Biomedical Engineering.