Published on in Vol 2, No 1 (2015): Jan-Jun

Usability and Acceptability of ASSESS MS: Assessment of Motor Dysfunction in Multiple Sclerosis Using Depth-Sensing Computer Vision

Usability and Acceptability of ASSESS MS: Assessment of Motor Dysfunction in Multiple Sclerosis Using Depth-Sensing Computer Vision

Usability and Acceptability of ASSESS MS: Assessment of Motor Dysfunction in Multiple Sclerosis Using Depth-Sensing Computer Vision

Journals

  1. D'Souza M, Van Munster C, Dorn J, Dorier A, Kamm C, Steinheimer S, Dahlke F, Uitdehaag B, Kappos L, Johnson M. Autoencoder as a New Method for Maintaining Data Privacy While Analyzing Videos of Patients With Motor Dysfunction: Proof-of-Concept Study. Journal of Medical Internet Research 2020;22(5):e16669 View
  2. D’Souza M, Steinheimer S, Dorn J, Morrison C, Boisvert J, Kravalis K, Burggraaff J, van Munster C, Diederich M, Sellen A, Kamm C, Dahlke F, Uitdehaag B, Kappos L. Reference videos reduce variability of motor dysfunction assessments in multiple sclerosis. Multiple Sclerosis Journal - Experimental, Translational and Clinical 2018;4(3):205521731879239 View
  3. Puh U, Hoehlein B, Deutsch J. Validity and Reliability of the Kinect for Assessment of Standardized Transitional Movements and Balance. Physical Medicine and Rehabilitation Clinics of North America 2019;30(2):399 View
  4. Cohen M. Connected health and multiple sclerosis. Revue Neurologique 2018;174(6):480 View
  5. Brichetto G, Pedullà L, Podda J, Tacchino A. Beyond center-based testing: Understanding and improving functioning with wearable technology in MS. Multiple Sclerosis Journal 2019;25(10):1402 View
  6. Morrison C, Huckvale K, Corish B, Dorn J, Kontschieder P, O’Hara K, Team A, Criminisi A, Sellen A. Assessing Multiple Sclerosis With Kinect: Designing Computer Vision Systems for Real-World Use. Human–Computer Interaction 2016;31(3-4):191 View
  7. Burggraaff J, Dorn J, D'Souza M, Morrison C, Kamm C, Kontschieder P, Tewarie P, Steinheimer S, Sellen A, Dahlke F, Kappos L, Uitdehaag B. Video-Based Pairwise Comparison: Enabling the Development of Automated Rating of Motor Dysfunction in Multiple Sclerosis. Archives of Physical Medicine and Rehabilitation 2020;101(2):234 View
  8. Parmar K, Stadelmann C, Rocca M, Langdon D, D'Angelo E, D’Souza M, Burggraaff J, Wegner C, Sastre-Garriga J, Barrantes-Freer A, Dorn J, Uitdehaag B, Montalban X, Wuerfel J, Enzinger C, Rovira A, Tintore M, Filippi M, Kappos L, Sprenger T. The role of the cerebellum in multiple sclerosis—150 years after Charcot. Neuroscience & Biobehavioral Reviews 2018;89:85 View
  9. Ploderer B, Fong J, Klaic M, Nair S, Vetere F, Cofré Lizama L, Galea M. How Therapists Use Visualizations of Upper Limb Movement Information From Stroke Patients: A Qualitative Study With Simulated Information. JMIR Rehabilitation and Assistive Technologies 2016;3(2):e9 View
  10. Marziniak M, Brichetto G, Feys P, Meyding-Lamadé U, Vernon K, Meuth S. The Use of Digital and Remote Communication Technologies as a Tool for Multiple Sclerosis Management: Narrative Review. JMIR Rehabilitation and Assistive Technologies 2018;5(1):e5 View
  11. Morrison C, Huckvale K, Corish B, Banks R, Grayson M, Dorn J, Sellen A, Lindley S. Visualizing Ubiquitously Sensed Measures of Motor Ability in Multiple Sclerosis. ACM Transactions on Interactive Intelligent Systems 2018;8(2):1 View
  12. Rasche L, Scheel M, Otte K, Althoff P, van Vuuren A, Gieß R, Kuchling J, Bellmann-Strobl J, Ruprecht K, Paul F, Brandt A, Schmitz-Hübsch T. MRI Markers and Functional Performance in Patients With CIS and MS: A Cross-Sectional Study. Frontiers in Neurology 2018;9 View
  13. van Munster C, D’Souza M, Steinheimer S, Kamm C, Burggraaff J, Diederich M, Kravalis K, Dorn J, Walsh L, Dahlke F, Kappos L, Uitdehaag B. Tasks of activities of daily living (ADL) are more valuable than the classical neurological examination to assess upper extremity function and mobility in multiple sclerosis. Multiple Sclerosis Journal 2019;25(12):1673 View
  14. D’Souza M, Papadopoulou A, Girardey C, Kappos L. Standardization and digitization of clinical data in multiple sclerosis. Nature Reviews Neurology 2021;17(2):119 View
  15. Asan O, Choudhury A. Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review. JMIR Human Factors 2021;8(2):e28236 View
  16. Papatheodorou N, Pino A, Kouroupetroglou G, Constantinides V, Andreadou E, Papageorgiou C. Upper Limb Motor Skills Performance Evaluation Based on Point-and-Click Cursor Trajectory Analysis: Application in Early Multiple Sclerosis Detection. IEEE Access 2019;7:28999 View
  17. Röhling H, Althoff P, Arsenova R, Drebinger D, Gigengack N, Chorschew A, Kroneberg D, Rönnefarth M, Ellermeyer T, Rosenkranz S, Heesen C, Behnia B, Hirano S, Kuwabara S, Paul F, Brandt A, Schmitz-Hübsch T. Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development and Usability Study. JMIR Human Factors 2022;9(2):e26825 View
  18. Röhling H, Otte K, Rekers S, Finke C, Rust R, Dorsch E, Behnia B, Paul F, Schmitz-Hübsch T. RGB-Depth Camera-Based Assessment of Motor Capacity: Normative Data for Six Standardized Motor Tasks. International Journal of Environmental Research and Public Health 2022;19(24):16989 View
  19. van Munster C, Burggraaff J, Steinheimer S, Kamm C, D’Souza M, Diederich M, Dorn J, Walsh L, Dahlke F, Kappos L, Uitdehaag B. Assessment of Multiple Aspects of Upper Extremity Function Independent From Ambulation in Patients With Multiple Sclerosis. International Journal of MS Care 2023;25(5):226 View