{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T22:28:28Z","timestamp":1762900108714,"version":"build-2065373602"},"reference-count":77,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,2,18]],"date-time":"2021-02-18T00:00:00Z","timestamp":1613606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000048","name":"American Cancer Society","doi-asserted-by":"publisher","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}],"id":[{"id":"10.13039\/100000048","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 \u00b1 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min\/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland\u2013Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes.<\/jats:p>","DOI":"10.3390\/s21041411","type":"journal-article","created":{"date-parts":[[2021,2,18]],"date-time":"2021-02-18T21:59:58Z","timestamp":1613685598000},"page":"1411","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4990-2999","authenticated-orcid":false,"given":"Sunku","family":"Kwon","sequence":"first","affiliation":[{"name":"Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA"}]},{"given":"Neng","family":"Wan","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Utah, Salt Lake City, UT 84112, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5933-4633","authenticated-orcid":false,"given":"Ryan D.","family":"Burns","sequence":"additional","affiliation":[{"name":"Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8234-3546","authenticated-orcid":false,"given":"Timothy A.","family":"Brusseau","sequence":"additional","affiliation":[{"name":"Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA"}]},{"given":"Youngwon","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong"},{"name":"MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0SL, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9273-0291","authenticated-orcid":false,"given":"Santosh","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Memphis, Memphis, TN 38152, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7815-0728","authenticated-orcid":false,"given":"Emre","family":"Ertin","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA"}]},{"given":"David W.","family":"Wetter","sequence":"additional","affiliation":[{"name":"Department of Population Health Sciences and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84132, USA"}]},{"given":"Cho Y.","family":"Lam","sequence":"additional","affiliation":[{"name":"Department of Population Health Sciences and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84132, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6397-3473","authenticated-orcid":false,"given":"Ming","family":"Wen","sequence":"additional","affiliation":[{"name":"Department of Sociology, University of Utah, Salt Lake City, UT 84112, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8893-960X","authenticated-orcid":false,"given":"Wonwoo","family":"Byun","sequence":"additional","affiliation":[{"name":"Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,18]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2011). mHealth: New Horizons for Health through Mobile Technologies, World Health Organization."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MC.2016.185","article-title":"Privacy and security in mobile health: A research agenda","volume":"49","author":"Kotz","year":"2016","journal-title":"Computer"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MC.2012.392","article-title":"Mobile health: Revolutionizing healthcare through transdisciplinary research","volume":"46","author":"Kumar","year":"2013","journal-title":"Computer"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e18","DOI":"10.2196\/mhealth.5027","article-title":"Smartloss: A personalized mobile health intervention for weight management and health promotion","volume":"4","author":"Martin","year":"2016","journal-title":"JMIR mHealth uHealth"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MPRV.2017.29","article-title":"Center of excellence for mobile sensor data-to-knowledge (MD2K)","volume":"16","author":"Kumar","year":"2017","journal-title":"IEEE Pervasive Comput."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1093\/jamia\/ocv056","article-title":"Center of excellence for mobile sensor data-to-knowledge (MD2K)","volume":"22","author":"Kumar","year":"2015","journal-title":"J. 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