{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T07:40:13Z","timestamp":1775547613199,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,5]],"date-time":"2021-08-05T00:00:00Z","timestamp":1628121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["2R42AG032748-04"],"award-info":[{"award-number":["2R42AG032748-04"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R42AG060853-01"],"award-info":[{"award-number":["1R42AG060853-01"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["2SB1AG032748-06"],"award-info":[{"award-number":["2SB1AG032748-06"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Health and Medical Research Council Australia","award":["1117061"],"award-info":[{"award-number":["1117061"]}]},{"name":"National Health and Medical Research Council Australia","award":["1180736"],"award-info":[{"award-number":["1180736"]}]},{"DOI":"10.13039\/501100003550","name":"Queensland Government","doi-asserted-by":"publisher","award":["Not applicable"],"award-info":[{"award-number":["Not applicable"]}],"id":[{"id":"10.13039\/501100003550","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Townsville Hospital and Health Services","award":["Not applicable"],"award-info":[{"award-number":["Not applicable"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Remote monitoring of physical frailty is important to personalize care for slowing down the frailty process and\/or for the healthy recovery of older adults following acute or chronic stressors. Taking the Fried frailty criteria as a reference to determine physical frailty and frailty phenotypes (slowness, weakness, exhaustion, inactivity), this study aimed to explore the benefit of machine learning to determine the least number of digital biomarkers of physical frailty measurable from a pendant sensor during activities of daily living. Two hundred and fifty-nine older adults were classified into robust or pre-frail\/frail groups based on the physical frailty assessments by the Fried frailty criteria. All participants wore a pendant sensor at the sternum level for 48 h. Of seventeen sensor-derived features extracted from a pendant sensor, fourteen significant features were used for machine learning based on logistic regression modeling and a recursive feature elimination technique incorporating bootstrapping. The combination of percentage time standing, percentage time walking, walking cadence, and longest walking bout were identified as optimal digital biomarkers of physical frailty and frailty phenotypes. These findings suggest that a combination of sensor-measured exhaustion, inactivity, and speed have potential to screen and monitor people for physical frailty and frailty phenotypes.<\/jats:p>","DOI":"10.3390\/s21165289","type":"journal-article","created":{"date-parts":[[2021,8,5]],"date-time":"2021-08-05T09:35:32Z","timestamp":1628156132000},"page":"5289","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Digital Biomarkers of Physical Frailty and Frailty Phenotypes Using Sensor-Based Physical Activity and Machine Learning"],"prefix":"10.3390","volume":"21","author":[{"given":"Catherine","family":"Park","sequence":"first","affiliation":[{"name":"Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9441-683X","authenticated-orcid":false,"given":"Ramkinker","family":"Mishra","sequence":"additional","affiliation":[{"name":"Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5779-8848","authenticated-orcid":false,"given":"Jonathan","family":"Golledge","sequence":"additional","affiliation":[{"name":"Queensland Research Centre for Peripheral Vascular Disease, Australian Institute of Tropical Medicine, College of Medicine and Dentistry, James Cook University, Townsville, QLD 4811, Australia"},{"name":"The Department of Vascular and Endovascular Surgery, The Townsville University Hospital, Townsville, QLD 4814, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0320-8101","authenticated-orcid":false,"given":"Bijan","family":"Najafi","sequence":"additional","affiliation":[{"name":"Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cger.2010.08.009","article-title":"The frailty syndrome: Definition and natural history","volume":"27","author":"Xue","year":"2011","journal-title":"Clin. Geriatr. Med."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"M146","DOI":"10.1093\/gerona\/56.3.M146","article-title":"Frailty in older adults: Evidence for a phenotype","volume":"56","author":"Fried","year":"2001","journal-title":"J. Gerontol. Ser. A Biol. Sci. Med. 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