{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T20:30:14Z","timestamp":1779136214147,"version":"3.51.4"},"reference-count":34,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"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 inactivity increases the risk of many adverse health conditions, including the world\u2019s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers\u2019 methods to monitor a patient\u2019s actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the two models on two physical movement datasets collected from several volunteers who carried tri-axial accelerometer sensors. The first dataset is from the UCI machine learning repository, which contains 14 different activities-of-daily-life (ADL) and is collected from 16 volunteers who carried a single wrist-worn tri-axial accelerometer. The second dataset includes ten other ADLs and is gathered from eight volunteers who placed the sensors on their hips. Our experiment results show that the RNN model provides accurate performance compared to the state-of-the-art methods in classifying the fundamental movement patterns with an overall accuracy of 84.89% and an overall F1-score of 82.56%. The results indicate that our method provides the medical doctors and trainers a promising way to track and understand a patient\u2019s physical activities precisely for better treatment.<\/jats:p>","DOI":"10.3390\/s21165564","type":"journal-article","created":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T22:51:00Z","timestamp":1629327060000},"page":"5564","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Deep Learning for Classifying Physical Activities from Accelerometer Data"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6911-8056","authenticated-orcid":false,"given":"Vimala","family":"Nunavath","sequence":"first","affiliation":[{"name":"Department of Science and Industry Systems, University of South-Eastern Norway, Hasbergsvei 36, Krona, 3616 Kongsberg, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sahand","family":"Johansen","sequence":"additional","affiliation":[{"name":"CAIR, Department of ICT, University of Agder, Jon Lilletunsvei 9, 4879 Grimstad, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tommy Sandtorv","family":"Johannessen","sequence":"additional","affiliation":[{"name":"CAIR, Department of ICT, University of Agder, Jon Lilletunsvei 9, 4879 Grimstad, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Jiao","sequence":"additional","affiliation":[{"name":"CAIR, Department of ICT, University of Agder, Jon Lilletunsvei 9, 4879 Grimstad, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bj\u00f8rge Herman","family":"Hansen","sequence":"additional","affiliation":[{"name":"Department of Sport Science and Physical Education, University of Agder, Universitetsveien 25, 4630 Kristiansand, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sveinung","family":"Berntsen","sequence":"additional","affiliation":[{"name":"Department of Sport Science and Physical Education, University of Agder, Universitetsveien 25, 4630 Kristiansand, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Morten","family":"Goodwin","sequence":"additional","affiliation":[{"name":"CAIR, Department of ICT, University of Agder, Jon Lilletunsvei 9, 4879 Grimstad, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Physical activity, exercise, and physical fitness: Definitions and distinctions for health-related research","volume":"100","author":"Caspersen","year":"1985","journal-title":"Public Health Rep."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kawaguchi, N., Nishio, N., Roggen, D., Inoue, S., Pirttikangas, S., and Van Laerhoven, K. 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