{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:22:10Z","timestamp":1760059330601,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T00:00:00Z","timestamp":1748995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006663","name":"National Institutes of Disability, Independent Living","doi-asserted-by":"publisher","award":["90REGE0004-01-00"],"award-info":[{"award-number":["90REGE0004-01-00"]}],"id":[{"id":"10.13039\/100006663","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Sobel-Duncan Border Health Research Award","award":["90REGE0004-01-00"],"award-info":[{"award-number":["90REGE0004-01-00"]}]},{"name":"University of Texas","award":["90REGE0004-01-00"],"award-info":[{"award-number":["90REGE0004-01-00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>This case series investigates whether traditional machine learning (ML) and convolutional neural network (CNN) models trained on wrist-worn accelerometry data collected in a laboratory setting can accurately predict real-world functional hand use in individuals with chronic stroke. Participants (N = 4) with neuroimaging-confirmed chronic stroke completed matched activity scripts\u2014comprising instrumental and basic activities of daily living\u2014in-lab and at-home. Participants wore ActiGraph CenterPoint Insight watches on the impaired and unimpaired wrists; concurrent video recordings were collected in both environments. Frame-by-frame annotations of the video, guided by the FAABOS scale (functional, non-functional, unknown), served as the ground truth. The results revealed a consistent capacity\u2013performance gap: participants used their impaired hand more in-lab than at-home, with the largest discrepancies in patients with moderate to severe impairment. Random forest ML models trained on in-lab accelerometry accurately classified at-home hand use, with the highest performance in mildly and severely impaired limbs (accuracy = 0.80\u20130.90) and relatively lower performance (accuracy = 0.62) in moderately impaired limbs. CNN models showed comparable accuracy to random forest classifiers. These pilot findings demonstrate the feasibility of using lab-trained ML models to monitor real-world hand use and identify emerging patterns of learned non-use\u2014enabling timely, targeted interventions to promote recovery in outpatient stroke rehabilitation.<\/jats:p>","DOI":"10.3390\/bioengineering12060615","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T08:51:04Z","timestamp":1749027064000},"page":"615","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Accelerometry and the Capacity\u2013Performance Gap: Case Series Report in Upper-Extremity Motor Impairment Assessment Post-Stroke"],"prefix":"10.3390","volume":"12","author":[{"given":"Estevan M.","family":"Nieto","sequence":"first","affiliation":[{"name":"Department of Rehabilitation Sciences, The University of Texas at El Paso, El Paso, TX 79968, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edaena","family":"Lujan","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The University of Texas at El Paso, El Paso, TX 79968, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Crystal A.","family":"Mendoza","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The University of Texas at El Paso, El Paso, TX 79968, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yazbel","family":"Arriaga","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The University of Texas at El Paso, El Paso, TX 79968, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cecilia","family":"Fierro","sequence":"additional","affiliation":[{"name":"Department of Occupational Therapy, The University of Texas at El Paso, El Paso, TX 79902, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tan","family":"Tran","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The Catholic University of America, Washington, DC 20064, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin-Ching","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The Catholic University of America, Washington, DC 20064, USA"},{"name":"Department of Informatics, New Jersey Institute of Technology, Newark, NJ 07102, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8823-3391","authenticated-orcid":false,"given":"Alvaro N.","family":"Gurovich","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy and Movement Sciences, The University of Texas at El Paso, El Paso, TX 79968, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4735-6114","authenticated-orcid":false,"given":"Peter S.","family":"Lum","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, The Catholic University of America, Washington, DC 20064, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0190-6923","authenticated-orcid":false,"given":"Shashwati","family":"Geed","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy and Movement Sciences, The University of Texas at El Paso, El Paso, TX 79968, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1177\/1545968307305353","article-title":"A standardized approach to performing the action research arm test","volume":"22","author":"Yozbatiran","year":"2008","journal-title":"Neurorehabil Neural Repair"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"13","DOI":"10.2340\/1650197771331","article-title":"The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance","volume":"7","author":"Jaasko","year":"1975","journal-title":"Scand. 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