{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T21:55:09Z","timestamp":1774994109442,"version":"3.50.1"},"reference-count":40,"publisher":"Human Kinetics","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"abstract":"<jats:p>\n                    <jats:italic>\n                      <jats:bold>Background<\/jats:bold>\n                      :\n                    <\/jats:italic>\n                    Epoch-level accelerometry summary metrics have the potential to be device-agnostic, meaning that similar estimates should be obtained regardless of the device used. The objective of this study was to identify which metric (Euclidean Norm Minus One [ENMO], mean amplitude deviation [MAD], and Monitor-Independent Movement Summary [MIMS] units) best harmonizes data across devices in an applied setting measuring children\u2019s activity.\n                    <jats:italic>\n                      <jats:bold>Methods<\/jats:bold>\n                      :\n                    <\/jats:italic>\n                    Children (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009239; 9.3\u2009\u00b1\u20092.1\u00a0years, 47% female, 30% Black) wore ActiGraph GT9X (+\/\u22128\u00a0g, 50\u00a0Hz) accelerometers and were randomized to wear two of three consumer wearables, including Apple Watch Series 7 (+\/\u221216\u00a0g, 50\u00a0Hz), Garmin Vivoactive 4S (+\/\u22128\u00a0g, 25\u00a0Hz), and Fitbit Sense (+\/\u22124\u00a0g, 50\u00a0Hz) on their nondominant wrist while participating in 60\u00a0min of simulated free-living activities (i.e.,\u00a0walking, running, and soccer). The standard deviation across\n                    <jats:italic>z<\/jats:italic>\n                    scores for ENMO, MAD, and MIMS of each device was calculated at the second level to quantify variability across devices. Lin\u2019s concordance correlation coefficient was calculated for each combination of devices by metric to determine agreement. Multilevel intraclass correlation coefficients were additionally used to quantify harmonization.\n                    <jats:italic>\n                      <jats:bold>Results<\/jats:bold>\n                      :\n                    <\/jats:italic>\n                    The standard deviation of\n                    <jats:italic>z<\/jats:italic>\n                    score across devices was the lowest, indicating better harmonization, for MAD (0.13\u2009\u00b1\u20090.23), followed by ENMO (0.24\u2009\u00b1\u20090.50), and then MIMS (0.26\u2009\u00b1\u20090.39). Lin\u2019s concordance correlation coefficient was strongest for MAD, with coefficients ranging from .89 to .96. Lin\u2019s concordance correlation coefficient for MIMS ranged from .70 to .83 and was lowest for ENMO, ranging from .62 to .76. Overall intraclass correlation coefficient was highest for MAD (.88), followed by MIMS (.73), and ENMO (.62).\n                    <jats:italic>\n                      <jats:bold>Conclusions<\/jats:bold>\n                      :\n                    <\/jats:italic>\n                    MAD appears to perform best at harmonizing across all the sampled research-grade and consumer devices in children.\n                  <\/jats:p>","DOI":"10.1123\/jmpb.2025-0002","type":"journal-article","created":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T23:37:10Z","timestamp":1755733030000},"source":"Crossref","is-referenced-by-count":1,"title":["The Ability of Monitor-Independent Movement Summary Units, Euclidean Norm Minus One, and Mean Amplitude Deviation to Harmonize Accelerometry Data Across Research-Grade and Consumer Wearable Devices During Simulated Free-Living Physical Activity in Children"],"prefix":"10.1123","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0625-1479","authenticated-orcid":true,"given":"Olivia L.","family":"Finnegan","sequence":"first","affiliation":[{"name":"Department of Exercise Science, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James W.","family":"White III","sequence":"additional","affiliation":[{"name":"Department of Exercise Science, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1909-8170","authenticated-orcid":true,"given":"Bridget","family":"Armstrong","sequence":"additional","affiliation":[{"name":"Department of Exercise Science, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizabeth L.","family":"Adams","sequence":"additional","affiliation":[{"name":"Department of Exercise Science, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0840-1680","authenticated-orcid":true,"given":"Sarah","family":"Burkart","sequence":"additional","affiliation":[{"name":"Department of Exercise Science, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael W.","family":"Beets","sequence":"additional","affiliation":[{"name":"Department of Exercise Science, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5990-394X","authenticated-orcid":true,"given":"Srihari","family":"Nelakuditi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zifei","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongpeng","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keagan P.","family":"Kiely","sequence":"additional","affiliation":[{"name":"Department of Exercise Science, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0939-4731","authenticated-orcid":true,"given":"Rahul","family":"Ghosal","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8358-1979","authenticated-orcid":true,"given":"Stuart J.","family":"Fairclough","sequence":"additional","affiliation":[{"name":"Department of Sport and Physical Activity, Edge Hill University, Ormskirk, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7132-9725","authenticated-orcid":true,"given":"Gregory J.","family":"Welk","sequence":"additional","affiliation":[{"name":"Department of Kinesiology, Iowa State University, Ames, IA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5889-974X","authenticated-orcid":true,"given":"R. 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