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      Extended reality to assess post-stroke manual dexterity: contrasts between the classic box and block test, immersive virtual reality with controllers, with hand-tracking, and mixed-reality tests

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          Abstract

          Background

          Recent technological advancements present promising opportunities to enhance the frequency and objectivity of functional assessments, aligning with recent stroke rehabilitation guidelines. Within this framework, we designed and adapted different manual dexterity tests in extended reality (XR), using immersive virtual reality (VR) with controllers (BBT-VR-C), immersive VR with hand-tracking (BBT-VR-HT), and mixed-reality (MD-MR).

          Objective

          This study primarily aimed to assess and compare the validity of the BBT-VR-C, BBT-VR-HT and MD-MR to assess post-stroke manual dexterity. Secondary objectives were to evaluate reliability, usability and to define arm kinematics measures.

          Methods

          A sample of 21 healthy control participants (HCP) and 21 stroke individuals with hemiparesis (IHP) completed three trials of the traditional BBT, the BBT-VR-C, BBT-VR-HT and MD-MR. Content validity of the different tests were evaluated by asking five healthcare professionals to rate the difficulty of performing each test in comparison to the traditional BBT. Convergent validity was evaluated through correlations between the scores of the traditional BBT and the XR tests. Test-retest reliability was assessed through correlations between the second and third trial and usability was assessed using the System Usability Scale (SUS). Lastly, upper limb movement smoothness (SPARC) was compared between IHP and HCP for both BBT-VR test versions.

          Results

          For content validity, healthcare professionals rated the BBT-VR-HT (0[0–1]) and BBT-MR (0[0–1]) as equally difficult to the traditional BBT, whereas they rated BBT-VR-C as more difficult than the traditional BBT (1[0–2]). For IHP convergent validity, the Pearson tests demonstrated larger correlations between the scores of BBT and BBT-VR-HT ( r = 0.94; p < 0.001), and BBT and MD-MR ( r = 0.95; p < 0.001) than BBT and BBT-VR-C ( r = 0.65; p = 0.001). BBT-VR-HT and MD-MR usability were both rated as excellent, with median SUS scores of 83[57.5–91.3] and 83[53.8–92.5] respectively. Excellent reliability was found for the BBT-VR-C (ICC = 0.96; p < 0.001), BBT-VR-HT (ICC = 0.96; p < 0.001) and BBT-MR (ICC = 0.99; p < 0.001). The usability of the BBT-VR-C was rated as good with a median SUS of 70[43.8–83.8]. Upper limb movements of HCP were significantly smoother than for IHP when completing either the BBT-VR-C (t = 2.05; p = 0.043) and the BBT-VR-HT (t = 5.21; p < 0.001).

          Conclusion

          The different XR manual tests are valid, short-term reliable and usable tools to assess post-stroke manual dexterity.

          Trial registration

          https://clinicaltrials.gov/ct2/show/NCT04694833; Unique identifier: NCT04694833, Date of registration: 11/24/2020.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12984-024-01332-x.

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          Most cited references54

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          A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research.

          Intraclass correlation coefficient (ICC) is a widely used reliability index in test-retest, intrarater, and interrater reliability analyses. This article introduces the basic concept of ICC in the content of reliability analysis.
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            Guidelines for Adult Stroke Rehabilitation and Recovery: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association

            The aim of this guideline is to provide a synopsis of best clinical practices in the rehabilitative care of adults recovering from stroke.
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              An Empirical Evaluation of the System Usability Scale

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                Author and article information

                Contributors
                thierry.lejeune@uclouvain.be
                Journal
                J Neuroeng Rehabil
                J Neuroeng Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central (London )
                1743-0003
                15 March 2024
                15 March 2024
                2024
                : 21
                : 36
                Affiliations
                [1 ]Centre interdisciplinaire de recherche en réadaptation et intégration sociale, Université Laval, ( https://ror.org/04sjchr03) Québec, Canada
                [2 ]Department of rehabilitation, Faculty of medicine, Laval University, ( https://ror.org/04sjchr03) Quebec, QC Canada
                [3 ]Neuro Musculo Skeletal Lab (NMSK), Secteur des Sciences de la Santé, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, ( https://ror.org/02495e989) Brussels, Belgium
                [4 ]Service de médecine physique et réadaptation, Cliniques universitaires Saint-Luc, ( https://ror.org/03s4khd80) Avenue Hippocrate 10, Brussels, 1200 Belgium
                [5 ]ECAM- Institut Supérieur Industriel, ( https://ror.org/019axjh19) Brussels, Belgium
                [6 ]Psychological Sciences Research Institute (IPSY), Université Catholique de Louvain, ( https://ror.org/02495e989) Louvain‑la‑Neuve, Belgium
                [7 ]Louvain Bionics, Université catholique de Louvain, ( https://ror.org/02495e989) Louvain-la-Neuve, Belgium
                Article
                1332
                10.1186/s12984-024-01332-x
                10941416
                38491540
                0ec461da-9642-431e-9725-01f8c2a59adf
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 6 November 2023
                : 3 March 2024
                Funding
                Funded by: Win2Wal
                Award ID: 1810108
                Award ID: 1810108
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Neurosciences
                stroke,virtual reality,augmented reality,upper extremity,patient outcome assessment
                Neurosciences
                stroke, virtual reality, augmented reality, upper extremity, patient outcome assessment

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