A virtual sEMG prosthetic hand development system based on LabVIEW and PCI-1710HG A/D card

Author

Wu, Zhiyong ; Niu, Haijun ; Li, Deyu ; Pu, Fang ; Fan, Yubo

Author_Institution

Sch. of Biol. Sci. & Med. Eng., Beihang Univ., Beijing, China

Volume

4

fYear

2010

fDate

16-18 Oct. 2010

Firstpage

1743

Lastpage

1745

Abstract

This paper introduces a virtual sEMG prosthetic hand development system based on LabVIEW. The system is aimed at finding proper method to correctly and promptly discriminate hand motions via sEMG. Waveform Length has been proved effective as extracted feature in this paper due to its high performance and short computing time. A back-propagation Neural Networks(BP Networks) is chosen as classifier in order to train the system automatically. The result shows that the performance of the whole system is successful when discriminating the following four hand motions: flexion and extension of the wrist, open and grasp of hand.

Keywords

backpropagation; dexterous manipulators; electromyography; neural nets; prosthetics; virtual instrumentation; LabVIEW; PCI-1710HG; back-propagation neural networks; extension; feature extraction; flexion; hand motions; prosthetic hand; sEMG; waveform length; Artificial neural networks; Band pass filters; Electromyography; Feature extraction; Instruments; Prosthetic hand; BP Networks; LabVIEW; Waveform Length; prosthetic hand; sEMG;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on

Conference_Location

Yantai

Print_ISBN

978-1-4244-6495-1

Type

conf

DOI

10.1109/BMEI.2010.5640048

Filename

5640048