Pattern Recognition of Finger Joint Angle for Intelligent Bionic Hand Using sEMG

Zhuo Jun Xu; Yan Tao Tian; Zhi Ming Yang; Yang Li

doi:10.4028/www.scientific.net/AMM.448-453.3561

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 448-453Pattern Recognition of Finger Joint Angle for...

Pattern Recognition of Finger Joint Angle for Intelligent Bionic Hand Using sEMG

Abstract:

Finger joint angle pattern recognition is significant for the development of an intelligent bionic hand. It makes the intelligent prosthesis understand the users intension more accurately and complete movements better. Surface electromyography signals have been widely used in intelligent bionics prosthesis research and rehabilitation medicine due to its advantages like high efficiency, convenient collection and non-invasive access. An improved grid-search method using a support vector machine has been proposed for the finger joint angle pattern recognition issue in surface electromyography signals. Pattern recognition for surface electromyography signals of index finger movement and metacarpophalangeal joint angle has been performed. Better classification performance was achieved through screening of feature vector combined with an improved grid-search support vector machine classification algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 448-453)

Pages:

3561-3565

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.448-453.3561

Citation:

Cite this paper

Online since:

October 2013

Authors:

Zhuo Jun Xu, Yan Tao Tian*, Zhi Ming Yang, Yang Li

Keywords:

Finger Joint Angle, Grid-Search SVM, Pattern Recognition, SEMG

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* - Corresponding Author

References

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