{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T17:20:28Z","timestamp":1793380828070,"version":"4.5.0"},"reference-count":18,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T00:00:00Z","timestamp":1678060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008943","name":"Schweizerische Stiftung f\u00fcr das Cerebral Gel\u00e4hmte Kind","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008943","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Robot. AI"],"abstract":"<jats:p><jats:bold>Introduction:<\/jats:bold> Measuring kinematic behavior during robot-assisted gait therapy requires either laborious set up of a marker-based motion capture system or relies on the internal sensors of devices that may not cover all relevant degrees of freedom. This presents a major barrier for the adoption of kinematic measurements in the normal clinical schedule. However, to advance the field of robot-assisted therapy many insights could be gained from evaluating patient behavior during regular therapies.<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold> For this reason, we recently developed and validated a method for extracting kinematics from recordings of a low-cost RGB-D sensor, which relies on a virtual 3D body model to estimate the patient\u2019s body shape and pose in each frame. The present study aimed to evaluate the robustness of the method to the presence of a lower limb exoskeleton. 10 healthy children without gait impairment walked on a treadmill with and without wearing the exoskeleton to evaluate the estimated body shape, and 8 custom stickers were placed on the body to evaluate the accuracy of estimated poses.<\/jats:p><jats:p><jats:bold>Results &amp;amp; Conclusion:<\/jats:bold> We found that the shape is generally robust to wearing the exoskeleton, and systematic pose tracking errors were around 5\u00a0mm. Therefore, the method can be a valuable measurement tool for the clinical evaluation, e.g., to measure compensatory movements of the trunk.<\/jats:p>","DOI":"10.3389\/frobt.2023.1155542","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T05:51:25Z","timestamp":1678081885000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Markerless motion tracking to quantify behavioral changes during robot-assisted gait training: A validation study"],"prefix":"10.3389","volume":"10","author":[{"given":"Florian","family":"van Dellen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikolas","family":"Hesse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rob","family":"Labruy\u00e8re","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,3,6]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1186\/s12984-019-0496-x","article-title":"The FreeD module for the Lokomat facilitates a physiological movement pattern in healthy people - a proof of concept study","volume":"16","author":"Aurich-Schuler","year":"2019","journal-title":"J. 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