Publication: Comparison study of muscular-contraction classification between independent component analysis and artificial neural network
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Issued Date
2008
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-67549107947
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
2008 International Symposium on Communications and Information Technologies, ISCIT 2008, p.468-472
Suggested Citation
Sueaseenak D., Wibirama S., Chanwimalueang T., Pintavirooj C., Sangworasil M. Comparison study of muscular-contraction classification between independent component analysis and artificial neural network. 2008 International Symposium on Communications and Information Technologies, ISCIT 2008, p.468-472. doi:10.1109/ISCIT.2008.4700236 Retrieved from: https://hdl.handle.net/20.500.14740/3796
Abstract
We developed a multi-channel electromyogram acquisition system using PSOC microcontroller to acquire multichannel EMG signals. An array of 4 x 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. © 2008 IEEE.
Subject(s)
Acquisition systems
ANN
ANN classification
Artificial Neural Network
B-spline interpolation technique
Comparison study
Computational time
Electromyogram
EMG
EMG signal
ICA
Multi-channel
Muscle contractions
Muscular contraction
PCA
Surface electrode
Surface mapping
Topological mapping
Backpropagation
Hemodynamics
Muscle
Neural networks
Shrinkage
Splines
Independent component analysis
ANN
ANN classification
Artificial Neural Network
B-spline interpolation technique
Comparison study
Computational time
Electromyogram
EMG
EMG signal
ICA
Multi-channel
Muscle contractions
Muscular contraction
PCA
Surface electrode
Surface mapping
Topological mapping
Backpropagation
Hemodynamics
Muscle
Neural networks
Shrinkage
Splines
Independent component analysis