DocumentCode :
636559
Title :
Long term stability of surface EMG pattern classification for prosthetic control
Author :
Amsuss, Sebastian ; Paredes, Liliana P. ; Rudigkeit, Nina ; Graimann, Bernhard ; Herrmann, Michael J. ; Farina, Dario
Author_Institution :
Dept. of Neurorehabilitation Eng., Georg August Univ., Göttingen, Germany
fYear :
2013
fDate :
3-7 July 2013
Firstpage :
3622
Lastpage :
3625
Abstract :
Long-term functioning of a hand prosthesis is crucial for its acceptance by patients with upper limb deficit. In this study the reliability over days of the performance of pattern classification approaches based on surface electromyography (sEMG) signal for the control of upper limb prostheses was investigated. Recordings of sEMG from the forearm muscles were obtained across five consecutive days from five healthy subjects. It was demonstrated that the classification performance decreased monotonically on average by 4.1% per day. It was also found that the accumulated error was confined to three of the eight movement classes investigated. This contribution gives insight on the long term behavior of pattern classification, which is crucial for commercial viability.
Keywords :
electromyography; medical control systems; medical signal processing; pattern classification; prosthetics; reliability; commercial viability; forearm muscles; hand prosthesis; long term functioning; long term stability; patient acceptance; prosthetic control; reliability; surface EMG pattern classification; surface electromyography; upper limb deficit; Accuracy; Electrodes; Electromyography; Pattern recognition; Prosthetics; Standards; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2013.6610327
Filename :
6610327
Link To Document :
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