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SkillAR allows the user to consider movement corrections independent of the head position. Therefore, the user can receive motor feedback comfortably without risking an incorrect exercise performance. Head-mounted displays represent versatile technologies for providing motor feedback regarding skill training. In contrast to room-mounted displays, HMDs are easily portable and wearable. That allows for in-situ feedback in many situations where this would otherwise not be possible. However, the spatial positioning of the 3D feedback is not trivial. On the one hand, the user needs to understand the relation between the body and the suggested corrections in the space. On the other hand, certain exercises demand a specific head positioning to minimize errors and injuries. Depending on the exercise and the type of feedback, these two aspects can be highly conflicting. The paper at hand presents a solution for augmented reality headsets, that provides continuous and omnipresent motor feedback comfortably while facilitating a correct exercise performance. In an in-subject user study with 39 participants, we could not detect a significant disadvantage to SkillAR compared to conventional feedback methods found in the literature regarding identification and execution time as well as identification accuracy, in addition to the apparent major advantages for user health and usability. Furthermore, we found that the users could identify the feedback on the HMD more accurately.<\/jats:p>","DOI":"10.1007\/s10055-025-01108-1","type":"journal-article","created":{"date-parts":[[2025,2,4]],"date-time":"2025-02-04T05:11:12Z","timestamp":1738645872000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["SkillAR: omnipresent in-situ feedback for motor skill training using AR"],"prefix":"10.1007","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7421-750X","authenticated-orcid":false,"given":"Florian","family":"Diller","sequence":"first","affiliation":[]},{"given":"Nico","family":"Henkel","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5200-8870","authenticated-orcid":false,"given":"Gerik","family":"Scheuermann","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6583-3092","authenticated-orcid":false,"given":"Alexander","family":"Wiebel","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,4]]},"reference":[{"key":"1108_CR1","unstructured":"World Physiotherapy: Annual Membership Census - Global Report (2023). https:\/\/world.physio\/sites\/default\/files\/2024-01\/AMC2023-Global.pdf"},{"issue":"6","key":"1108_CR2","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.1097\/j.pain.0000000000000160","volume":"156","author":"RD Treede","year":"2015","unstructured":"Treede RD, Rief W, Barke A, Aziz Q, Bennett MI, Benoliel R, Cohen M, Evers S, Finnerup NB, First MB, Giamberardino MA, Kaasa S, Kosek E, Lavand\u2019homme P, Nicholas M, Perrot S, Scholz J, Schug S, Smith BH, Svensson P, Vlaeyen JWS, Wang SJ (2015) A classification of chronic pain for ICD-11. 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