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Based on multiple kernel learning (MKL) support vector machine and decision tree combined strategy, a multi-class classification method is proposed to classify lower limb motions using electromyography (EMG) signals. According to the framework of multiple kernel learning, the MKL-based multi-classifier is constructed using binary tree decomposition method. Four-channel surface EMG signals are firstly...
The application of hidden Markov model (HMM) to recognize gait phase using electromyographic (EMG) signals is described. Four time-domain features are extracted within a time segment of each channel of EMG signals to preserve pattern structure. According to the division of the gait cycle, the structure of HMM is determined, in which each state is associated with a gait phase. A modified Baum-Welch...
This paper describes the application of hidden Markov model (HMM) to recognition of gait mode based on electromyographic (EMG) signals. Four types of time-domain features were extracted from the EMG signals of selected muscles within a time segment. According to the division of the gait phase, the structure of HMM was determined, in which each state is associated with a gait phase. A modified Baum-Welch...
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