{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T20:49:10Z","timestamp":1772830150693,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,3,10]],"date-time":"2017-03-10T00:00:00Z","timestamp":1489104000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Physical activity monitoring algorithms are often developed using conditions that do not represent real-life activities, not developed using the target population, or not labelled to a high enough resolution to capture the true detail of human movement. We have designed a semi-structured supervised laboratory-based activity protocol and an unsupervised free-living activity protocol and recorded 20 older adults performing both protocols while wearing up to 12 body-worn sensors. Subjects\u2019 movements were recorded using synchronised cameras (\u226525 fps), both deployed in a laboratory environment to capture the in-lab portion of the protocol and a body-worn camera for out-of-lab activities. Video labelling of the subjects\u2019 movements was performed by five raters using 11 different category labels. The overall level of agreement was high (percentage of agreement &gt;90.05%, and Cohen\u2019s Kappa, corrected kappa, Krippendorff\u2019s alpha and Fleiss\u2019 kappa &gt;0.86). A total of 43.92 h of activities were recorded, including 9.52 h of in-lab and 34.41 h of out-of-lab activities. A total of 88.37% and 152.01% of planned transitions were recorded during the in-lab and out-of-lab scenarios, respectively. This study has produced the most detailed dataset to date of inertial sensor data, synchronised with high frame-rate (\u226525 fps) video labelled data recorded in a free-living environment from older adults living independently. This dataset is suitable for validation of existing activity classification systems and development of new activity classification algorithms.<\/jats:p>","DOI":"10.3390\/s17030559","type":"journal-article","created":{"date-parts":[[2017,3,10]],"date-time":"2017-03-10T09:39:55Z","timestamp":1489138795000},"page":"559","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["A Physical Activity Reference Data-Set Recorded from Older Adults Using Body-Worn Inertial Sensors and Video Technology\u2014The ADAPT Study Data-Set"],"prefix":"10.3390","volume":"17","author":[{"given":"Alan","family":"Bourke","sequence":"first","affiliation":[{"name":"Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Espen","family":"Ihlen","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronny","family":"Bergquist","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Per","family":"Wik","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Beatrix","family":"Vereijken","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0214-9290","authenticated-orcid":false,"given":"Jorunn","family":"Helbostad","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,10]]},"reference":[{"key":"ref_1","unstructured":"United Nations Department of Economic and Social Affairs, Population Division (2015). 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