Research on muscle fatigue identification technology based on ReliefF-NOSCA-AdakNN
To address the problem of muscle fatigue monitoring in competitive sport training,a surface electromyography(sEMG)feature extraction and classification algorithm based on ReliefF-NOSCA-AdakNN(RNA)was proposed.The analysis of the relevance between features and classes with the heuristic search algorithm,were combined by this algorithm.Besides,high-dimensional features were effectively selected and classified.The RNA algorithm was applied to the filtered biceps brachii sEMG data to identify and classify different fatigue states.The experimental results showed that the proposed RNA algorithm significantly outperformed the traditional single algorithms in terms of average classification accuracy and standard deviation,which reached 83.88%and 0.0127 respectively,demonstrating a good classification performance.
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