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- W2034678441 abstract "We developed a multi-channel electromyogram acquisition system using PSOC microcontroller to acquire multi-channel EMG signals. An array of 4 times 4 surface electrodes was used to record the EMG signal. The obtained signals were classified by a back-propagation-type artificial neural network. B-spline interpolation technique has been utilized to map the EMG signal on the muscle surface. The topological mapping of the EMG is then analyzed to classify the pattern of muscle contraction using independent component analysis. The proposed system was successfully demonstrated to record EMG data and its surface mapping. The comparison study of muscular contraction classification using independent component analysis and artificial neural network demonstrates shows that performance of ANN classification is as comparable as that of the ICA. The computational time of ANN is also less than that of the ICA." @default.
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- W2034678441 date "2008-10-01" @default.
- W2034678441 modified "2023-10-14" @default.
- W2034678441 title "Comparison Study of Muscular-Contraction Classification Between Independent Component Analysis and Artificial Neural Network" @default.
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- W2034678441 doi "https://doi.org/10.1109/iscit.2008.4700236" @default.
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