Analytical and Cross-Sectional Clinical Validity of a Smartphone-Based U-Turn Test in Multiple Sclerosis
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| Format: | Preprint |
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2025
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| author | Płonka, Marta Klimas, Rafał Stanev, Dimitar Angelini, Lorenza Napiórkowski, Natan Chan, Gabriela González Bunn, Lisa Glazier, Paul S Hosking, Richard Freeman, Jenny Hobart, Jeremy Zanon, Mattia Marsden, Jonathan Craveiro, Licinio Rinderknecht, Mike D |
| author_facet | Płonka, Marta Klimas, Rafał Stanev, Dimitar Angelini, Lorenza Napiórkowski, Natan Chan, Gabriela González Bunn, Lisa Glazier, Paul S Hosking, Richard Freeman, Jenny Hobart, Jeremy Zanon, Mattia Marsden, Jonathan Craveiro, Licinio Rinderknecht, Mike D |
| contents | Background: Gait and balance impairment can profoundly impact people with multiple sclerosis (PwMS). Objectives: To evaluate the analytical and clinical validity of the U-Turn Test (UTT), a smartphone-based assessment of dynamic balance in PwMS. Methods: The GaitLab study (ISRCTN15993728) enrolled adult PwMS (EDSS 0.0-6.5). PwMS performed the UTT in a gait laboratory (supervised) using 6 smartphones at different wear locations and daily during a two-week remote period (unsupervised) using one smartphone (belt front). Median turn speed was computed per UTT. In the supervised setting, turn detection accuracy of smartphones was compared to motion capture (mocap) via F1 scores. Agreement between smartphone- and mocap-derived turn speed was assessed by Bland-Altman and ICC(3,1). In the unsupervised setting, test-retest reliability (ICC[2,1]) and correlations with Timed 25-Foot Walk (T25FW), EDSS, Ambulation Score, 12-item Multiple Sclerosis Walking Scale (MSWS-12), and Activities-specific Balance Confidence scale (ABC) were evaluated. Results: Ninety-six PwMS were included. Turn speed was comparable across supervised (1.44 rad/s) and unsupervised settings (1.47 rad/s). In the supervised setting, turn detection was highly accurate (F1 >95% across wear locations). Turn speed agreement with mocap was high (ICC[3,1]: 0.87-0.92), with minimal bias (-0.04 to 0.11 rad/s). Unsupervised test-retest reliability (ICC[2,1]) was >0.90 when aggregating >=2 tests. Turn speed correlated with T25FW (rho=-0.79), EDSS (rho=-0.75), Ambulation score (rho=-0.73), MSWS-12 (rho=-0.65), and ABC (rho=-0.61). Conclusion: The UTT accurately and reproducibly measures turn speed across wear locations and settings, providing complementary dynamic balance insights to clinical measures and showing potential for use in multiple sclerosis trials. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_04914 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Analytical and Cross-Sectional Clinical Validity of a Smartphone-Based U-Turn Test in Multiple Sclerosis Płonka, Marta Klimas, Rafał Stanev, Dimitar Angelini, Lorenza Napiórkowski, Natan Chan, Gabriela González Bunn, Lisa Glazier, Paul S Hosking, Richard Freeman, Jenny Hobart, Jeremy Zanon, Mattia Marsden, Jonathan Craveiro, Licinio Rinderknecht, Mike D Signal Processing 92C55, 68T10, 93C85 I.5.4; J.3; H.1.2 Background: Gait and balance impairment can profoundly impact people with multiple sclerosis (PwMS). Objectives: To evaluate the analytical and clinical validity of the U-Turn Test (UTT), a smartphone-based assessment of dynamic balance in PwMS. Methods: The GaitLab study (ISRCTN15993728) enrolled adult PwMS (EDSS 0.0-6.5). PwMS performed the UTT in a gait laboratory (supervised) using 6 smartphones at different wear locations and daily during a two-week remote period (unsupervised) using one smartphone (belt front). Median turn speed was computed per UTT. In the supervised setting, turn detection accuracy of smartphones was compared to motion capture (mocap) via F1 scores. Agreement between smartphone- and mocap-derived turn speed was assessed by Bland-Altman and ICC(3,1). In the unsupervised setting, test-retest reliability (ICC[2,1]) and correlations with Timed 25-Foot Walk (T25FW), EDSS, Ambulation Score, 12-item Multiple Sclerosis Walking Scale (MSWS-12), and Activities-specific Balance Confidence scale (ABC) were evaluated. Results: Ninety-six PwMS were included. Turn speed was comparable across supervised (1.44 rad/s) and unsupervised settings (1.47 rad/s). In the supervised setting, turn detection was highly accurate (F1 >95% across wear locations). Turn speed agreement with mocap was high (ICC[3,1]: 0.87-0.92), with minimal bias (-0.04 to 0.11 rad/s). Unsupervised test-retest reliability (ICC[2,1]) was >0.90 when aggregating >=2 tests. Turn speed correlated with T25FW (rho=-0.79), EDSS (rho=-0.75), Ambulation score (rho=-0.73), MSWS-12 (rho=-0.65), and ABC (rho=-0.61). Conclusion: The UTT accurately and reproducibly measures turn speed across wear locations and settings, providing complementary dynamic balance insights to clinical measures and showing potential for use in multiple sclerosis trials. |
| title | Analytical and Cross-Sectional Clinical Validity of a Smartphone-Based U-Turn Test in Multiple Sclerosis |
| topic | Signal Processing 92C55, 68T10, 93C85 I.5.4; J.3; H.1.2 |
| url | https://arxiv.org/abs/2512.04914 |