DocumentCode
2107790
Title
The evaluation of the discriminant ability of multiclass SVM in a study of hand motion recognition by using SEMG
Author
Futamata, M. ; Nagata, Kazuyuki ; Magatani, K.
Author_Institution
Sch. of Eng., Course of Electr. & Electron. Syst., Tokai Univ., Kumamoto, Japan
fYear
2012
fDate
Aug. 28 2012-Sept. 1 2012
Firstpage
5246
Lastpage
5249
Abstract
Electromyogram (EMG) is a kind of biological signal that is generated because of excitement of muscle according to the motor instruction from a brain. We have been experimentally developing the hand motion recognition system by using 4 channels forearm EMG signals. In our system, in order to classify measured EMG SVM (Support Vector Machine) that has higher discriminability is used. Often SVM is used as a non-linear classifier. But, In the conventional system that we developed, we used a canonical discriminant analysis (CDA) method. CDA method is linear discriminant function, but it has shown good experimental results. Therefore, we have compared the discriminant ability between SVM and CDA. In this report, we will describe about the results of this experiment.
Keywords
electromyography; medical signal processing; pattern classification; statistical analysis; support vector machines; CDA method; EMG SVM; SEMG; biological signal; canonical discriminant analysis method; discriminant ability; electromyogram; forearm EMG signals; hand motion recognition system; linear discriminant function; motor instruction; multiclass SVM; nonlinear classifier; support vector machine; Electrodes; Electromyography; Equations; Kernel; Pattern recognition; Support vector machines; Algorithms; Diagnosis, Computer-Assisted; Discriminant Analysis; Electromyography; Hand; Humans; Movement; Muscle Contraction; Muscle, Skeletal; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Support Vector Machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location
San Diego, CA
ISSN
1557-170X
Print_ISBN
978-1-4244-4119-8
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/EMBC.2012.6347177
Filename
6347177
Link To Document