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We aimed to develop an open-source gait recognition for older adults using sensor data and explore the effect of data augmentation on model training. A convolutional neural network was trained using lower-back inertial sensor data from 20 participants (mean age 76.4) and externally validated on 47 participants (mean age 72.3). The model was trained using 6-channel data (accelerations and angular velocities) and 3-channel data (accelerations only), with and without data augmentation. On the testing dataset, the best 6-channel model achieved accuracy of 91.4%, precision of 59.7%, sensitivity of 99.5%, F1-score of 74.7%, and specificity of 90.3%, and the best 3-channel model achieved accuracy of 96.5%, precision of 78.7%, sensitivity of 98.9%, F1-score of 87.6%, and specificity of 96.1%. On the external validation dataset, the best models with both channels show near-perfect scores. This study demonstrates that the convolutional neural network algorithm based on lower-back inertial sensor data can accurately recognize daily-life gait of older adults, and data augmentation was especially beneficial for models using acceleration data only.<\/jats:p>\n                  <jats:p>\n                    <jats:bold>Graphical abstract<\/jats:bold>\n                  <\/jats:p>","DOI":"10.1007\/s11517-025-03466-z","type":"journal-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T05:16:12Z","timestamp":1761110172000},"page":"483-491","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["An open-source, externally validated neural network algorithm to recognize daily-life gait of older adults based on a lower-back sensor"],"prefix":"10.1007","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7440-0371","authenticated-orcid":false,"given":"Yuge","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Sjoerd M.","family":"Bruijn","sequence":"additional","affiliation":[]},{"given":"Michiel","family":"Punt","sequence":"additional","affiliation":[]},{"given":"Jorunn L.","family":"Helbostad","sequence":"additional","affiliation":[]},{"given":"Mirjam","family":"Pijnappels","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9741-7202","authenticated-orcid":false,"given":"Sina","family":"David","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,22]]},"reference":[{"key":"3466_CR1","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1016\/j.pmr.2017.06.006","volume":"28","author":"R Cuevas-Trisan","year":"2017","unstructured":"Cuevas-Trisan R (2017) Balance problems and fall risks in the elderly. 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Helbostad and Dr. Espen Alexander F. Ihlen, with the data handled and provided by Dr. Sabato Melone. The Regional Committee on Ethics in Medical Research in Central Norway approved the trial protocol and participants provided written informed consent.The external validation data provided by the Research Group Lifestyle and Health at Utrecht University of Applied Sciences, Utrecht, the Netherlands. The ethical approval was granted by the medical ethical review committee of Utrecht (METC number: 20\u2013462\/C) and participants provided written informed consent.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}