| A method for the control of multigrasp myoelectric prosthetic hands. | |
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MedLine Citation:
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PMID: 22180515 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation. |
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Authors:
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Skyler Ashton Dalley; Huseyin Atakan Varol; Michael Goldfarb |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural Date: 2011-12-12 |
Journal Detail:
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Title: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Volume: 20 ISSN: 1558-0210 ISO Abbreviation: IEEE Trans Neural Syst Rehabil Eng Publication Date: 2012 Jan |
Date Detail:
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Created Date: 2012-01-24 Completed Date: 2012-05-21 Revised Date: 2012-05-24 |
Medline Journal Info:
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Nlm Unique ID: 101097023 Medline TA: IEEE Trans Neural Syst Rehabil Eng Country: United States |
Other Details:
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Languages: eng Pagination: 58-67 Citation Subset: IM |
Affiliation:
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Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37240, USA. skyler.a.dalley@gmail.com |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Biomechanics Calibration Computer Systems Data Collection Electrodes Electromyography / methods* Electronics Fingers / physiology Hand* Hand Strength / physiology* Humans Motion Muscle Contraction / physiology Prostheses and Implants* Prosthesis Design / methods* User-Computer Interface |
| Grant Support | |
ID/Acronym/Agency:
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1R21 HD068753-01/HD/NICHD NIH HHS; R21 HD068753/HD/NICHD NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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