A comparison of post-processing techniques on the performance of EMG based pattern recognition system for the transradial amputees

Al-Timemy, AH; Khushaba, RN; Escudero, J

A comparison of post-processing techniques on the performance of EMG based pattern recognition system for the transradial amputees

Al-Timemy, AH Khushaba, RN

Escudero, J

Permalink

Publication Type:: Conference Proceeding
Citation:: Middle East Conference on Biomedical Engineering, MECBME, 2016, 2016-November pp. 46 - 49
Issue Date:: 2016-11-15

Closed Access

	Filename	Description	Size
	Amputees paper.pdf	Published version	415.31 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Al-Timemy, AH	en_US
dc.contributor.author	Khushaba, RN https://orcid.org/0000-0001-8528-8979	en_US
dc.contributor.author	Escudero, J	en_US
dc.date.issued	2016-11-15	en_US
dc.identifier.citation	Middle East Conference on Biomedical Engineering, MECBME, 2016, 2016-November pp. 46 - 49	en_US
dc.identifier.isbn	9781509025558	en_US
dc.identifier.issn	2165-4247	en_US
dc.identifier.uri	http://hdl.handle.net/10453/99943
dc.description.abstract	© 2016 IEEE. Pattern recognition control applied on surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for the control of powered prosthetics for transradial amputees. The use of limb prostheses is essential for maintaining personal independence and a more effective inclusion in society. However, due to their poor control, imposed by the reduced accuracy of hand movement classification, EMG-driven upper limb prostheses are still not widely used. Hence, post-processing techniques were proposed to reduce the misclassification rates. In this paper, we investigate the effect of two post-processing techniques, namely majority vote and Bayesian fusion, on the performance of EMG-based PR systems when applied on amputees. We measured the effectiveness of a number of time and frequency-based feature extraction methods with different post-processing techniques and various numbers of voting decisions. EMG data was collected from four transradial amputees while imagining seven classes of hand movements. Our results suggested that the recently proposed Time Domain Power-Spectral Descriptors (TD-PSD) can significantly enhance the performance of EMG pattern recognition and that the use of the suggested post-processing techniques can further enhance the performance of EMG-based PR systems, with error rates of approximately 5% on average across all amputees. Additionally, in problems with a large number of EMG channels, no significant differences were observed between the performance of both Bayesian fusion and majority vote.	en_US
dc.relation.ispartof	Middle East Conference on Biomedical Engineering, MECBME	en_US
dc.relation.isbasedon	10.1109/MECBME.2016.7745405	en_US
dc.title	A comparison of post-processing techniques on the performance of EMG based pattern recognition system for the transradial amputees	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2016-November	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2016-November	en_US

Abstract:

© 2016 IEEE. Pattern recognition control applied on surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for the control of powered prosthetics for transradial amputees. The use of limb prostheses is essential for maintaining personal independence and a more effective inclusion in society. However, due to their poor control, imposed by the reduced accuracy of hand movement classification, EMG-driven upper limb prostheses are still not widely used. Hence, post-processing techniques were proposed to reduce the misclassification rates. In this paper, we investigate the effect of two post-processing techniques, namely majority vote and Bayesian fusion, on the performance of EMG-based PR systems when applied on amputees. We measured the effectiveness of a number of time and frequency-based feature extraction methods with different post-processing techniques and various numbers of voting decisions. EMG data was collected from four transradial amputees while imagining seven classes of hand movements. Our results suggested that the recently proposed Time Domain Power-Spectral Descriptors (TD-PSD) can significantly enhance the performance of EMG pattern recognition and that the use of the suggested post-processing techniques can further enhance the performance of EMG-based PR systems, with error rates of approximately 5% on average across all amputees. Additionally, in problems with a large number of EMG channels, no significant differences were observed between the performance of both Bayesian fusion and majority vote.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/99943