NDLI: Examining the adverse effects of limb position on pattern recognition based myoelectric control

Content Provider	IEEE Xplore Digital Library
Author	Scheme, E. Fougner, A. Stavdahl, Ø. Chan, A.D.C. Englehart, K.
Copyright Year	2010
Description	Author affiliation: Department of Systems & Computer Engineering at Carleton University, ON Canada (Chan, A.D.C.) \|\| Institute of Biomedical Engineering at the University of New Brunswick, Fredericton, Canada (Scheme, E.; Englehart, K.) \|\| Department of Engineering Cybernetics at the Norwegian University of Science and Technology, Trondheim, Norway (Fougner, A.; Stavdahl, Ø.)
Abstract	Pattern recognition of myoelectric signals for the control of prosthetic devices has been widely reported and debated. A large portion of the literature focuses on offline classification accuracy of pre-recorded signals. Historically, however, there has been a semantic gap between research findings and a clinically viable implementation. Recently, renewed focus on prosthetics research has pushed the field to provide more clinically relevant outcomes. One way to work towards this goal is to examine the differences between research and clinical results. The constrained nature in which offline training and test data is often collected compared to the dynamic nature of prosthetic use is just one example. In this work, we demonstrate that variations in limb position after training can have a substantial impact on the robustness of myoelectric pattern recognition.
Starting Page	6337
Ending Page	6340
File Size	410617
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5627638
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electromyography Prosthetics Pattern recognition Training Accuracy Accelerometers Elbow
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Tracking training evolution: Patient with upper limb amputation above the elbow

Towards better understanding and reducing the effect of limb position on myoelectric upper-limb prostheses

Protocol for site selection and movement assessment for the myoelectric control of a multi-functional upper-limb prosthesis

Improving myoelectric pattern recognition positional robustness using advanced training protocols

Control of a myoelectric arm considering cooperated motion of elbow and shoulder joints

Using speech for mode selection in control of multifunctional myoelectric prostheses

Prosthesis-guided training of pattern recognition-controlled myoelectric prosthesis

Pattern recognition control outperforms conventional myoelectric control in upper limb patients with targeted muscle reinnervation

A multi-modal approach for hand motion classification using surface EMG and accelerometers

Examining the adverse effects of limb position on pattern recognition based myoelectric control

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Protocol for site selection and movement assessment for the myoelectric control of a multi-functional upper-limb prosthesis

Improving myoelectric pattern recognition positional robustness using advanced training protocols

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