DocumentCode :
285070
Title :
A subband coding scheme and the Bayesian neural network for EMG function analysis
Author :
Cheng, Kuo-Sheng ; Chan, Din-yuen ; Liou, Sheeng-borng
Author_Institution :
Inst. of Biomed. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Volume :
2
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
931
Abstract :
A subband coding scheme and Bayesian neural network (BNN) approach to the analysis of electromyographic (EMG) signals of upper extremity limb functions are presented. Three channels of EMG signals recorded from the biceps, triceps and one muscle of the forearm are used for discriminating six primitive motions associated with the limb. A set of parameters is extracted from the spectrum of the EMG signals combining with the subband coding technique for data compression. Each sequence of EMG signals is cut into five frames from the primary point located by the energy threshold method. From each frame, the parameters are then obtained by the integration of the subbands. The temporal as well as the spectral characteristics can be implicitly or directly included in the parameters. The BNN is used as a subnet for discriminating one motion. From the results, it is shown that an average recognition rate of 85% may be achieved
Keywords :
bioelectric potentials; biology computing; biomechanics; data compression; muscle; neural nets; Bayesian neural network; EMG function analysis; biology computing; data compression; energy threshold method; spectral characteristics; subband coding; temporal characteristics; upper extremity limb functions; Artificial neural networks; Band pass filters; Bayesian methods; Biomedical engineering; Electromyography; Extremities; Muscles; Neural networks; Probability; Sampling methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.226868
Filename :
226868
Link To Document :
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