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dc.contributor.author Lock, Blair A.
dc.contributor.author Schultz, Aimee E.
dc.contributor.author Kuiken, Todd A.
dc.date.accessioned 2010-07-29T17:03:12Z
dc.date.available 2010-07-29T17:03:12Z
dc.date.issued 2008
dc.identifier.citation Proceedings of the MEC’08 conference, UNB; 2008. en_US
dc.identifier.uri http://hdl.handle.net/10161/2795
dc.description.abstract The promise of pattern recognition for improved control of upper-extremity powered prostheses has existed for a long time. During the years of offline research and algorithm development, very little experience has been gained with real-time use in clinical and chronic settings. Our group, having the benefit of working with subjects who have undergone targeted muscle reinnervation (TMR) surgery, is at the forefront of real-world application of pattern recognition for upper extremity amputees. Based on our experiences, we highlight a progression of myoelectric control schemes from conventional control to enhanced pattern recognition control, stressing the application of simple pattern recognition schemes to replace more conventional control. These clinically practical pattern recognition systems incorporate a realistic number of electrodes and the ability to control available prosthetic components. Our experience suggests how the impending, and initial deployment of pattern recognition-controlled prostheses for daily use can be more approachable than what is depicted in high-dimension studies common in the literature today. en_US
dc.language.iso en_US en_US
dc.publisher Myoelectric Symposium en_US
dc.subject myoelectric prosthesis en_US
dc.subject pattern recognition en_US
dc.title CLINICALLY PRACTICAL APPLICATIONS OF PATTERN RECOGNITION FOR MYOELECTRIC PROSTHESES en_US
dc.type Article en_US

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