{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T10:24:18Z","timestamp":1787048658098,"version":"build-2736575974"},"reference-count":34,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["ZS\/2023\/11\/181945"],"award-info":[{"award-number":["ZS\/2023\/11\/181945"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Accurate gait event detection using inertial measurement units (IMUs) is essential for temporal gait analysis, but frame-level detection is challenged by sparse initial contact (IC) and foot-off (FO) events. This study evaluated recurrent neural network architectures and training strategies for simultaneous IC and FO detection using a single shank-mounted smartphone IMU. The internal dataset included 28 healthy older adults and 18 individuals with non-specific low back pain (NSLBP). Temporal label expansion substantially improved validation performance for gated recurrent unit (GRU) and long short-term memory models, whereas point-label and class-weighted training performed poorly. The selected label-expanded GRU (LE-GRU) achieved F1 scores above 0.95 for both events and mean absolute temporal errors below 12 ms on held-out internal test folds, with high performance in both cohorts. On an external dataset with different sensor and acquisition characteristics, high performance required full-network fine-tuning, indicating the need for adaptation across datasets. Stance phase and stride time calculated from LE-GRU-predicted events showed high agreement with reference-derived values, with Lin\u2019s concordance correlation coefficients from 0.980 to 0.994. These findings demonstrate that temporal label expansion enables accurate GRU-based gait event detection and temporal gait analysis from data collected with a single smartphone IMU.<\/jats:p>","DOI":"10.3390\/bioengineering13080924","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T15:48:36Z","timestamp":1786722516000},"page":"924","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning-Based Temporal Gait Analysis Using a Smartphone IMU in Older Adults with and Without Non-Specific Low Back Pain"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5370-3090","authenticated-orcid":false,"given":"Gerome","family":"Vivar","sequence":"first","affiliation":[{"name":"Health and Physical Activity, Otto von Guericke University Magdeburg, 39104 Magdeburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7010-5768","authenticated-orcid":false,"given":"Shivam","family":"Singh","sequence":"additional","affiliation":[{"name":"Health and Physical Activity, Otto von Guericke University Magdeburg, 39104 Magdeburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5375-9748","authenticated-orcid":false,"given":"Tobias","family":"Bea","sequence":"additional","affiliation":[{"name":"Health and Physical Activity, Otto von Guericke University Magdeburg, 39104 Magdeburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Saal","sequence":"additional","affiliation":[{"name":"Health and Physical Activity, Otto von Guericke University Magdeburg, 39104 Magdeburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3584-4986","authenticated-orcid":false,"given":"Victor","family":"Munoz-Martel","sequence":"additional","affiliation":[{"name":"Health and Physical Activity, Otto von Guericke University Magdeburg, 39104 Magdeburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0421-0796","authenticated-orcid":false,"given":"Lutz","family":"Schega","sequence":"additional","affiliation":[{"name":"Health and Physical Activity, Otto von Guericke University Magdeburg, 39104 Magdeburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.gaitpost.2011.03.027","article-title":"Efficacy of clinical gait analysis: A systematic review","volume":"34","author":"Wren","year":"2011","journal-title":"Gait Posture"},{"key":"ref_2","first-page":"560","article-title":"Gait analysis: Clinical facts","volume":"52 4","author":"Baker","year":"2016","journal-title":"Eur. 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