{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:10:49Z","timestamp":1772554249338,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,9,28]],"date-time":"2021-09-28T00:00:00Z","timestamp":1632787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Turkish Ministry of Education","award":["n\/a"],"award-info":[{"award-number":["n\/a"]}]},{"DOI":"10.13039\/100001288","name":"Parkinson's Foundation","doi-asserted-by":"publisher","award":["PF-FBS-1898-18-21"],"award-info":[{"award-number":["PF-FBS-1898-18-21"]}],"id":[{"id":"10.13039\/100001288","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001288","name":"Parkinson's Foundation","doi-asserted-by":"publisher","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}],"id":[{"id":"10.13039\/100001288","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wearable inertial measurement units (IMUs) are used in gait analysis due to their discrete wearable attachment and long data recording possibilities within indoor and outdoor environments. Previously, lower back and shin\/shank-based IMU algorithms detecting initial and final contact events (ICs-FCs) were developed and validated on a limited number of healthy young adults (YA), reporting that both IMU wear locations are suitable to use during indoor and outdoor gait analysis. However, the impact of age (e.g., older adults, OA), pathology (e.g., Parkinson\u2032s Disease, PD) and\/or environment (e.g., indoor vs. outdoor) on algorithm accuracy have not been fully investigated. Here, we examined IMU gait data from 128 participants (72-YA, 20-OA, and 36-PD) to thoroughly investigate the suitability of ICs-FCs detection algorithms (1 \u00d7 lower back and 1 \u00d7 shin\/shank-based) for quantifying temporal gait characteristics depending on IMU wear location and walking environment. The level of agreement between algorithms was investigated for different cohorts and walking environments. Although mean temporal characteristics from both algorithms were significantly correlated for all groups and environments, subtle but characteristically nuanced differences were observed between cohorts and environments. The lowest absolute agreement level was observed in PD (ICC2,1 = 0.979, 0.806, 0.730, 0.980) whereas highest in YA (ICC2,1 = 0.987, 0.936, 0.909, 0.989) for mean stride, stance, swing, and step times, respectively. Absolute agreement during treadmill walking (ICC2,1 = 0.975, 0.914, 0.684, 0.945), indoor walking (ICC2,1 = 0.987, 0.936, 0.909, 0.989) and outdoor walking (ICC2,1 = 0.998, 0.940, 0.856, 0.998) was found for mean stride, stance, swing, and step times, respectively. Findings of this study suggest that agreements between algorithms are sensitive to the target cohort and environment. Therefore, researchers\/clinicians should be cautious while interpreting temporal parameters that are extracted from inertial sensors-based algorithms especially for those with a neurological condition.<\/jats:p>","DOI":"10.3390\/s21196476","type":"journal-article","created":{"date-parts":[[2021,9,28]],"date-time":"2021-09-28T21:39:29Z","timestamp":1632865169000},"page":"6476","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson\u2019s Populations"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3384-4213","authenticated-orcid":false,"given":"Yunus","family":"Celik","sequence":"first","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6846-9372","authenticated-orcid":false,"given":"Sam","family":"Stuart","sequence":"additional","affiliation":[{"name":"Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8698-7605","authenticated-orcid":false,"given":"Wai Lok","family":"Woo","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4049-9291","authenticated-orcid":false,"given":"Alan","family":"Godfrey","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/s00508-016-1096-4","article-title":"Gait disorders in adults and the elderly","volume":"129","author":"Pirker","year":"2017","journal-title":"Wien. 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