This paper is in the following e-collection/theme issue:

Digital Health Reviews (1724) New Methods (1134) Wearable Devices and Sensors (1133) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732) mHealth for Data Collection and Research (1196) Mobile Health (mhealth) (3464)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44428, first published .
Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

Authors of this article:

Tim Woelfle1, 2 Author Orcid Image ;   Lucie Bourguignon3 Author Orcid Image ;   Johannes Lorscheider1, 2 Author Orcid Image ;   Ludwig Kappos1, 2 Author Orcid Image ;   Yvonne Naegelin1, 2 Author Orcid Image ;   Catherine Ruth Jutzeler3 Author Orcid Image
Article Authors Cited by (34) Tweetations (14) Metrics

Journals

  1. Rego S, Henriques A, Serra S, Costa T, Rodrigues A, Nunes F. Methods for the Clinical Validation of Digital Endpoints: Protocol for a Scoping Review Abstract. JMIR Research Protocols 2023;12:e47119 View
  2. de Queiroz R, Alves J, Sasaki J. Digital Biomarkers in the Assessment of Mobility in Individuals with Multiple Sclerosis. Sclerosis 2023;1(3):134 View
  3. Woelfle T, Pless S, Reyes Ó, Wiencierz A, Kappos L, Granziera C, Lorscheider J. Smartwatch-derived sleep and heart rate measures complement step counts in explaining established metrics of MS severity. Multiple Sclerosis and Related Disorders 2023;80:105104 View
  4. Bannwart M. Präzisionsrehabilitation im Neuroreha-Alltag. neuroreha 2023;15(04):194 View
  5. Masanneck L, Pawlitzki M, Meuth S. Digitale Medizin in der neurologischen Forschung – zwischen Hype und Evidenz. Der Nervenarzt 2024;95(3):230 View
  6. González-Castro A, Leirós-Rodríguez R, Prada-García C, Benítez-Andrades J. The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review. Journal of Medical Internet Research 2024;26:e54934 View
  7. Podda J, Pedullà L, Brichetto G, Tacchino A. Evaluating Cognitive-Motor Interference in Multiple Sclerosis: A Technology-Based Approach. Bioengineering 2024;11(3):277 View
  8. Tryfonos C, Chrysafi M, Papadopoulou S, Vadikolias K, Spanoudaki M, Mentzelou M, Fotiou D, Pavlidou E, Gkouvas G, Vorvolakos T, Michailidis A, Bisbinas A, Alexatou O, Giaginis C. Association of Mediterranean diet adherence with disease progression, quality of life and physical activity, sociodemographic and anthropometric parameters, and serum biomarkers in community-dwelling older adults with multiple sclerosis: a cross-sectional study. Aging Clinical and Experimental Research 2024;36(1) View
  9. Macias Alonso A, Hirt J, Woelfle T, Janiaud P, Hemkens L. Definitions of digital biomarkers: a systematic mapping of the biomedical literature. BMJ Health & Care Informatics 2024;31(1):e100914 View
  10. Wyatt J, Guo C. From Research to Application of Wearable-Derived Digital Health Measures—A Perspective From ActiGraph. Journal for the Measurement of Physical Behaviour 2024;7(1) View
  11. Grijalvo M, Ordieres-Meré J, Villalba-Díez J, Aladro-Benito Y, Martín-Ávila G, Simon-Hurtado A, Vivaracho-Pascual C. Sufficiency for PSS tracking gait disorders in multiple sclerosis: A managerial perspective. Heliyon 2024;10(9):e30001 View
  12. Zubair A. Utilization of wearable technology to track functional changes in a patient with myopathy. Brain Circulation 2024;10(2):190 View
  13. Jafleh E, Alnaqbi F, Almaeeni H, Faqeeh S, Alzaabi M, Al Zaman K. The Role of Wearable Devices in Chronic Disease Monitoring and Patient Care: A Comprehensive Review. Cureus 2024 View
  14. Rauzi M, Akay R, Balakrishnan S, Piper C, Gobert D, Flach A. Current State of Connected Sensor Technologies Used During Rehabilitation Care: Protocol for a Scoping Review. JMIR Research Protocols 2024;13:e60496 View
  15. Carpinella I, Bertoni R, Anastasi D, Cardini R, Lencioni T, Ferrarin M, Cattaneo D, Gervasoni E. Walk Longer! Using Wearable Inertial Sensors to Uncover Which Gait Aspects Should Be Treated to Increase Walking Endurance in People with Multiple Sclerosis. Sensors 2024;24(22):7284 View
  16. De Angelis F, Nistri R, Wright S. Measuring Disease Progression in Multiple Sclerosis Clinical Drug Trials and Impact on Future Patient Care. CNS Drugs 2025;39(1):55 View
  17. Schönherr C, Ziegler J, Zentek T, Rashid A, Strauss S, Tallner A, Grothe M. Smartphone-based gait analysis in the assessment of fatigue and fatigability in people with multiple sclerosis: a supervised cohort study. Journal of Neurology 2025;272(3) View
  18. Monaghan P, VanNostrand M, Takla T, Fritz N. Predicting Real-World Physical Activity in Multiple Sclerosis: An Integrated Approach Using Clinical, Sensor-Based, and Self-Reported Measures. Sensors 2025;25(6):1780 View
  19. Yadav S, Bukke S, Prajapati S, Singh A, Chettupalli A, Nicholas B. Nanobiosensors in neurodegenerative disease diagnosis: A promising pathway for early detection. DIGITAL HEALTH 2025;11 View
  20. Sun Y, Chen J, Ji M, Li X. Wearable Technologies for Health Promotion and Disease Prevention in Older Adults: Systematic Scoping Review and Evidence Map. Journal of Medical Internet Research 2025;27:e69077 View
  21. Zheng M, Miao L, Bu Y, Larivière V. Understanding discrepancies in the coverage of OpenAlex: The case of China. Journal of the Association for Information Science and Technology 2025;76(11):1591 View
  22. Masurkar P, Rikame S. Gait assessment using wearable technologies in neurological disorders: a rapid umbrella. Neurodegenerative Disease Management 2025:1 View
  23. Schriefer D, Dillenseger A, Atta Y, Inojosa H, Ziemssen T. From implementation to discontinuation: multi-year experience with the multiple sclerosis performance test as a digital monitoring tool. Frontiers in Digital Health 2025;7 View
  24. Dibben G, Santillan C, Brage S, Buman M, Duncan E, Granat M, Hillsdon M, Martin A, Matthews C, McCrorie P, Taylor R, Vasankari T, Foster C. Reporting of Accelerometry in Health Research: A Scoping Review of Current Guidance. Scandinavian Journal of Medicine & Science in Sports 2025;35(10) View
  25. Filippatou A, Mowry E. Sensors in Multiple Sclerosis. Current Neurology and Neuroscience Reports 2025;25(1) View
  26. Goldman M, Chen S, Kunisetty B, Gelfand J, Cree B, Block V. Validating wearable step counts in multiple sclerosis research: a replication study. Frontiers in Neurology 2025;16 View
  27. Al-Ewaidat O, Naffaa M. Emerging AI- and Biomarker-Driven Precision Medicine in Autoimmune Rheumatic Diseases: From Diagnostics to Therapeutic Decision-Making. Rheumato 2025;5(4):17 View
  28. Marchiori M, Heidler J, Segantin G, Eckmann H, Chinapaw M, Kjærgaard M, Schipperijn J. Visualising accelerometer-based 24/7 human movement behaviour data: an umbrella review and framework development from the LABDA project. Journal of Activity, Sedentary and Sleep Behaviors 2025;4(1) View

Books/Policy Documents

  1. Vullers B, Smid J, Pashalis G, Goutzounis D, Lourakis E, Neves N. Digital Sustainability: Inclusion and Transformation. View
  2. Wadhwa G, Bossoufi B. Integrating AI With Haptic Systems for Smarter Healthcare Solutions. View
  3. . Diagnostik und Therapie neurologischer Erkrankungen. View
  4. Ziemssen T, Voigt I. Diagnostik und Therapie neurologischer Erkrankungen. View

Conference Proceedings

  1. Dove G, Guthmann M, Charvet L, Nov O, Pilloni G. Designing Interactive Systems Conference. "Data Is One Thing, But I Want To Know The Story Behind": Designing For Self-Tracking and Remote Patient Monitoring In The Context Of Multiple Sclerosis Care View
  2. Arunachalam N, Devi S, A N, S N, Meikandan M. 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IoT Wearable Medical Device for Heart Disease Recognition Based Ml and Dl: A Bovw Based MDCNN Classification Approach View