{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T02:54:44Z","timestamp":1790736884571,"version":"4.1.0"},"reference-count":17,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"vor","delay-in-days":85,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"P&K Foundation, Switzerland"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J NeuroEngineering Rehabil"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Objective measurement of upper-limb movement quality based on biomechanical data collected in clinical routine has the potential to enable precision neurorehabilitation at scale. However, integrating biomechanical data collection into daily clinical workflows remains challenging. In this exploratory study, we evaluated the usability of two technologies for routine kinematic data collection: an IMU-based version of the instrumented Action Research Arm Test (iARAT-IMU) and a MMC markerless motion capture (MMC) system. First, five physiotherapists independently operated the iARAT-IMU across seven clinical routine assessment sessions at a rehabilitation clinic in Switzerland to quantify learning curves, setup times, and usability. Second, we conducted a preference study in which the same therapists used both, the IMU- and MMC-system, during a standardized drinking task and completed quantitative and qualitative usability assessments focusing on system preference and underlying reasons. Results show that therapists rapidly learned to operate the tablet application for scoring the iARAT; however, the IMU system added approximately 11\u00a0min of setup time and sometimes required assistance. In contrast, the MMC workflow required approximately 2\u00a0min of additional time - well within the 5-minute maximum indicated a priori by therapists as acceptable for clinical routine and received consistently higher usability ratings. Most therapists preferred this approach due to greater efficiency and reduced patient burden. These findings highlight important design considerations for future digital assessment tools and indicate that MMC systems may offer a more feasible pathway toward routine biomechanical data collection for upper-limb assessments in clinical neurorehabilitation.<\/jats:p>","DOI":"10.1186\/s12984-026-02075-7","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T13:25:53Z","timestamp":1783430753000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards routine biomechanical data collection in stroke rehabilitation: a usability comparison of IMU and markerless motion capture systems for functional upper-limb assessments"],"prefix":"10.1186","volume":"23","author":[{"given":"Tim","family":"Unger","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Schmitt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lea","family":"Cebulla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chris","family":"Easthope Awai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,7]]},"reference":[{"issue":"5","key":"2075_CR1","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1177\/1747493017711813","volume":"12","author":"G Kwakkel","year":"2017","unstructured":"Kwakkel G, Lannin NA, Borschmann K, English C, Ali M, Churilov L, et al. Standardized measurement of sensorimotor recovery in stroke trials: consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable. Int J Stroke. 2017;12(5):451\u201361. https:\/\/doi.org\/10.1177\/1747493017711813.","journal-title":"Int J Stroke"},{"issue":"8","key":"2075_CR2","doi-asserted-by":"publisher","first-page":"783","DOI":"10.1177\/1747493019873519","volume":"14","author":"G Kwakkel","year":"2019","unstructured":"Kwakkel G, Van Wegen E, Burridge J, Winstein C, Dokkum L, Alt Murphy M, et al. Standardized measurement of quality of upper limb movement after stroke: consensus-based core recommendations from the Second Stroke Recovery and Rehabilitation Roundtable. Int J Stroke. 2019;14(8):783\u201391. https:\/\/doi.org\/10.1177\/1747493019873519.","journal-title":"Int J Stroke"},{"issue":"5","key":"2075_CR3","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1177\/1747493017711816","volume":"12","author":"J Bernhardt","year":"2017","unstructured":"Bernhardt J, Hayward KS, Kwakkel G, Ward NS, Wolf SL, Borschmann K, et al. Agreed definitions and a shared vision for new standards in stroke recovery research: the Stroke Recovery and Rehabilitation Roundtable taskforce. Int J Stroke. 2017;12(5):444\u201350. https:\/\/doi.org\/10.1177\/1747493017711816.","journal-title":"Int J Stroke"},{"issue":"3","key":"2075_CR4","doi-asserted-by":"publisher","first-page":"718","DOI":"10.1161\/STROKEAHA.118.023531","volume":"50","author":"A Schwarz","year":"2019","unstructured":"Schwarz A, Kanzler CM, Lambercy O, Luft AR, Veerbeek JM. Systematic Review on Kinematic Assessments of Upper Limb Movements After Stroke. Stroke. 2019;50(3):718\u201327. https:\/\/doi.org\/10.1161\/STROKEAHA.118.023531.","journal-title":"Stroke"},{"issue":"1","key":"2075_CR5","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1038\/s41746-020-00328-w","volume":"3","author":"C Adans-Dester","year":"2020","unstructured":"Adans-Dester C, Hankov N, O\u2019Brien A, Vergara-Diaz G, Black-Schaffer R, Zafonte R, et al. Enabling precision rehabilitation interventions using wearable sensors and machine learning to track motor recovery. npj Dig Med. 2020;3(1):121. https:\/\/doi.org\/10.1038\/s41746-020-00328-w.","journal-title":"npj Dig Med"},{"key":"2075_CR6","doi-asserted-by":"publisher","unstructured":"Weikert T, Roellin E, P\u00e9rez-Serrano M, Du E, Heumos L, Theis FJ, Paez-Granados D, Awai CE. Embedding computational neurorehabilitation in clinical practice using a modular intelligent health system. arXiv. arXiv:2503.18732 (2025). https:\/\/doi.org\/10.48550\/arXiv.2503.18732 . 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