Index Finger Motion Recognition Using Self-Advise Support Vector Machine

Publisher:
Massey University
Publication Type:
Journal Article
Citation:
International Journal On Smart Sensing and Intelligent Systems, 2014, 7 (2), pp. 644 - 657 (14)
Issue Date:
2014-06
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Because of the functionality of an index finger, the disability of its motion in the modern age can decrease the person’s quality of life. As a part of rehabilitation therapy, the recognition of the index finger motion for rehabilitation purposes should be done properly. This paper proposes a novel recognition system of the index finger motion suing a cutting-edge method and its improvements. The proposed system consists of combination of feature extraction method, a dimensionality reduction and well-known classifier, Support Vector Machine (SVM). An improvement of SVM, Self-advise SVM (SA-SVM), is tested to evaluate and compare its performance with the original one. The experimental result shows that SA-SVM improves the classification performance by on average 0.63 %.
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