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CLINICALLY PRACTICAL APPLICATIONS OF PATTERN RECOGNITION FOR MYOELECTRIC PROSTHESES

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Date
2008
Authors
Lock, Blair A.
Schultz, Aimee E.
Kuiken, Todd A.
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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.
Type
Other article
Subject
myoelectric prosthesis
pattern recognition
Permalink
https://hdl.handle.net/10161/2795
Citation
Proceedings of the MEC’08 conference, UNB; 2008.
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  • MEC Symposium Conference Proceedings
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Copyright 2002, 2005 and 2008, The University of New Brunswick.

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License. Creative Commons License

Rights for Collection: MEC Symposium Conference Proceedings


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