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The assessment after rehabilitation is an important part of rehabilitation medicine, and of great significance for the basic research and clinical application for rehabilitation medicine. Physician can make objective analysis about patients’ present conditions, and then appropriate training program can be developed for patients to recover their body function more effectively. Three kinds of EMG signal, that is, the healthy, patient with myopathy, and patient with neuropathy, are involved. The complexity of the three types of signal is compared and the related variables (embedding dimension and time delay of phase space reconstruction) are determined by singular-value decomposition and mutual information method. Moreover, a novel effective approach improved from Hilbert-Huang Transform (HHT) is proposed here for the further comparision among the three EMG signals. The results show both methods can distinguish the three kinds of EMG signal clearly.

Rehabilitation Assessment Based on the Complexity and Fluctuation of EMG Signal