{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T22:19:16Z","timestamp":1778624356574,"version":"3.51.4"},"reference-count":29,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T00:00:00Z","timestamp":1617753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["401741517"],"award-info":[{"award-number":["401741517"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Increased levels of light, moderate and vigorous physical activity (PA) are positively associated with health benefits. Therefore, sensor-based human activity recognition can identify different types and levels of PA. In this paper, we propose a two-layer locomotion recognition method using dynamic time warping applied to inertial sensor data. Based on a video-validated dataset (ADAPT), which included inertial sensor data recorded at the lower back (L5 position) during an unsupervised task-based free-living protocol, the recognition algorithm was developed, validated and tested. As a first step, we focused on the identification of locomotion activities walking, ascending and descending stairs. These activities are difficult to differentiate due to a high similarity. The results showed that walking could be recognized with a sensitivity of 88% and a specificity of 89%. Specificity for stair climbing was higher compared to walking, but sensitivity was noticeably decreased. In most cases of misclassification, stair climbing was falsely detected as walking, with only 0.2\u20135% not assigned to any of the chosen types of locomotion. Our results demonstrate a promising approach to recognize and differentiate human locomotion within a variety of daily activities.<\/jats:p>","DOI":"10.3390\/s21082601","type":"journal-article","created":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T21:49:06Z","timestamp":1617832146000},"page":"2601","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Template-Based Recognition of Human Locomotion in IMU Sensor Data Using Dynamic Time Warping"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9972-904X","authenticated-orcid":false,"given":"Kim S.","family":"Sczuka","sequence":"first","affiliation":[{"name":"Department of Clinical Gerontology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376 Stuttgart, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marc","family":"Schneider","sequence":"additional","affiliation":[{"name":"Department of Clinical Gerontology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376 Stuttgart, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alan K.","family":"Bourke","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, NTNU, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7688-0188","authenticated-orcid":false,"given":"Sabato","family":"Mellone","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic, and Information Engineering, University of Bologna, 40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5992-3681","authenticated-orcid":false,"given":"Ngaire","family":"Kerse","sequence":"additional","affiliation":[{"name":"Department of General Practice and Primary Health Care, University of Auckland, Auckland 1023, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0214-9290","authenticated-orcid":false,"given":"Jorunn L.","family":"Helbostad","sequence":"additional","affiliation":[{"name":"Department of Neuroscience, NTNU, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Clemens","family":"Becker","sequence":"additional","affiliation":[{"name":"Department of Clinical Gerontology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376 Stuttgart, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5987-447X","authenticated-orcid":false,"given":"Jochen","family":"Klenk","sequence":"additional","affiliation":[{"name":"Department of Clinical Gerontology, Robert-Bosch-Hospital, Auerbachstr. 110, 70376 Stuttgart, Germany"},{"name":"Institute of Epidemiology and Medical Biometry, Ulm University, Helmholtzstr. 22, 89081 Ulm, Germany"},{"name":"Study Center Stuttgart, IB University for Health and Social Sciences, Paulinenstr. 45, 70178 Stuttgart, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,7]]},"reference":[{"key":"ref_1","unstructured":"(2009). 1.\tPhysical Activity Guidelines Advisory Committee report, 2008. 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