{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T04:10:37Z","timestamp":1769314237389,"version":"3.49.0"},"reference-count":72,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2020,12,3]],"date-time":"2020-12-03T00:00:00Z","timestamp":1606953600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007900","name":"University of Central Florida","doi-asserted-by":"crossref","award":["VPR-AECR Award"],"award-info":[{"award-number":["VPR-AECR Award"]}],"id":[{"id":"10.13039\/100007900","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Establishing a natural communication interface between the user and the terminal device is one of the central challenges of hand neuroprosthetics research. Surface electromyography (EMG) is the most common source of neural signals for interpreting a user\u2019s intent in these interfaces. However, how the capacity of EMG generation is affected by various clinical parameters remains largely unknown. In this study, we examined the EMG activity of forearm muscles recorded from 11 transradially amputated subjects who performed a wide range of movements. EMG recordings from 40 able-bodied subjects were also analyzed to provide comparative benchmarks. By using non-negative matrix factorization, we extracted the synergistic EMG patterns for each subject to estimate the dimensionality of muscle control, under the framework of motor synergies. We found that amputees exhibited less than four synergies (with substantial variability related to the length of remaining limb and age), whereas able-bodied subjects commonly demonstrate five or more synergies. The results of this study provide novel insight into the muscle synergy framework and the design of natural myoelectric control interfaces.<\/jats:p>","DOI":"10.1371\/journal.pone.0242921","type":"journal-article","created":{"date-parts":[[2020,12,3]],"date-time":"2020-12-03T18:37:05Z","timestamp":1607020625000},"page":"e0242921","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":8,"title":["Dimensionality analysis of forearm muscle activation for myoelectric control in transradial amputees"],"prefix":"10.1371","volume":"15","author":[{"given":"Alexander","family":"McClanahan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Moench","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4421-0742","authenticated-orcid":true,"given":"Qiushi","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2020,12,3]]},"reference":[{"key":"pone.0242921.ref001","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1016\/j.apmr.2007.11.005","article-title":"Estimating the Prevalence of Limb Loss in the United States: 2005 to 2050","volume":"89","author":"K Ziegler-Graham","year":"2008","journal-title":"Arch Phys Med Rehabil"},{"key":"pone.0242921.ref002","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1080\/03093640600994581","article-title":"Upper limb prosthesis use and abandonment: a survey of the last 25 years","volume":"31","author":"EA Biddiss","year":"2007","journal-title":"Prosthet Orthot Int"},{"key":"pone.0242921.ref003","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1007\/s40137-013-0044-8","article-title":"Prosthetic Myoelectric Control Strategies: A Clinical Perspective","volume":"2","author":"AD Roche","year":"2014","journal-title":"Curr Surg Reports"},{"key":"pone.0242921.ref004","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1109\/TNSRE.2014.2305111","article-title":"The extraction of neural information from the surface EMG for the control of upper-limb prostheses: Emerging avenues and challenges","volume":"22","author":"D Farina","year":"2014","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"pone.0242921.ref005","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1682\/JRRD.2010.09.0177","article-title":"Electromyogram pattern recognition for control of powered upper-limb prostheses: State of the art and challenges for clinical use","volume":"48","author":"EJ Scheme","year":"2011","journal-title":"J Rehabil Res Dev"},{"key":"pone.0242921.ref006","doi-asserted-by":"crossref","first-page":"1128","DOI":"10.1109\/TBME.2007.909536","article-title":"Online electromyographic control of a robotic prosthesis","volume":"55","author":"P Shenoy","year":"2008","journal-title":"IEEE Trans Biomed Eng"},{"key":"pone.0242921.ref007","first-page":"1154","article-title":"Repeatability of grasp recognition for robotic hand prosthesis control based on sEMG data.","author":"F Palermo","year":"2017","journal-title":"IEEE Int Conf Rehabil Robot"},{"key":"pone.0242921.ref008","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1109\/TNSRE.2009.2039590","article-title":"Multiple binary classifications via linear discriminant analysis for improved controllability of a powered prosthesis","volume":"18","author":"LJ Hargrove","year":"2010","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"pone.0242921.ref009","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fnbot.2016.00009","article-title":"Deep learning with convolutional neural networks applied to electromyography data: A resource for the classification of movements for prosthetic hands","volume":"10","author":"M Atzori","year":"2016","journal-title":"Front Neurorobot"},{"key":"pone.0242921.ref010","first-page":"3354","article-title":"A comparison of proportional control methods for pattern recognition control","author":"AM Simon","year":"2011","journal-title":"Proc Annu Int Conf IEEE Eng Med Biol Soc EMBS"},{"key":"pone.0242921.ref011","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1109\/TNSRE.2014.2361478","article-title":"A multi-class proportional myocontrol algorithm for upper limb prosthesis control: Validation in real-life scenarios on amputees","volume":"23","author":"S Amsuess","year":"2015","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"pone.0242921.ref012","unstructured":"COAPT. 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