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

Wearable Devices and Sensors (706) Mobile Health (mhealth) (2238)

Published on in Vol 8 , No 10 (2020) :October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22108, first published .
Evaluating the Utility of Smartphone-Based Sensor Assessments in Persons With Multiple Sclerosis in the Real-World Using an App (elevateMS): Observational, Prospective Pilot Digital Health Study

Evaluating the Utility of Smartphone-Based Sensor Assessments in Persons With Multiple Sclerosis in the Real-World Using an App (elevateMS): Observational, Prospective Pilot Digital Health Study

Evaluating the Utility of Smartphone-Based Sensor Assessments in Persons With Multiple Sclerosis in the Real-World Using an App (elevateMS): Observational, Prospective Pilot Digital Health Study

Authors of this article:

Abhishek Pratap 1 Author Orcid Image ;   Daniel Grant 2 Author Orcid Image ;   Ashok Vegesna 2 Author Orcid Image ;   Meghasyam Tummalacherla 1 Author Orcid Image ;   Stanley Cohan 3 Author Orcid Image ;   Chinmay Deshpande 2 Author Orcid Image ;   Lara Mangravite 1 Author Orcid Image ;   Larsson Omberg 1 Author Orcid Image
Article Authors Cited by (29) Tweetations (24) Metrics

Journals

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  2. Inojosa H, Akgün K, Haacke K, Ziemssen T. MSProDiscuss – Entwicklung eines digitalen Tools zur standardisierten Patientenanamnese, um Progredienz bei Multipler Sklerose zu identifizieren. Fortschritte der Neurologie · Psychiatrie 2021;89(07/08):374 View
  3. Palotai M, Wallack M, Kujbus G, Dalnoki A, Guttmann C. Usability of a Mobile App for Real-Time Assessment of Fatigue and Related Symptoms in Patients With Multiple Sclerosis: Observational Study. JMIR mHealth and uHealth 2021;9(4):e19564 View
  4. Abou L, Wong E, Peters J, Dossou M, Sosnoff J, Rice L. Smartphone applications to assess gait and postural control in people with multiple sclerosis: A systematic review. Multiple Sclerosis and Related Disorders 2021;51:102943 View
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  7. Alonso R, Eizaguirre M, López P, Silva B, Rojas J, Sinay V, Tkachuk V, Patrucco L, Carra A, Bruno D, Pagani Cassara F, Fernández Liguori N, Tavolini D, Camerlingo S, Garcea O, Galiani A, Mainella C, Barboza A, Luetic G, Carnero Contentti E. Argentinean consensus recommendations for the use of telemedicine in clinical practice in adult people with multiple sclerosis. Neurological Sciences 2023;44(2):667 View
  8. . MindKind: A mixed-methods protocol for the feasibility of global digital mental health studies in young people. Wellcome Open Research 2022;6:275 View
  9. Lam K, Bucur I, van Oirschot P, de Graaf F, Strijbis E, Uitdehaag B, Heskes T, Killestein J, de Groot V. Personalized monitoring of ambulatory function with a smartphone 2-minute walk test in multiple sclerosis. Multiple Sclerosis Journal 2023;29(4-5):606 View
  10. Daniore P, Nittas V, von Wyl V. Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal. Journal of Medical Internet Research 2022;24(9):e39910 View
  11. Gopal A, Hsu W, Allen D, Bove R. Remote Assessments of Hand Function in Neurological Disorders: Systematic Review. JMIR Rehabilitation and Assistive Technologies 2022;9(1):e33157 View
  12. Michaud J, Penny C, Cull O, Hervet E, Chamard-Witkowski L. Remote Testing Apps for Multiple Sclerosis Patients: Scoping Review of Published Articles and Systematic Search and Review of Public Smartphone Apps. JMIR Neurotechnology 2023;2:e37944 View
  13. Bonnechère B, Rintala A, Spooren A, Lamers I, Feys P. Is mHealth a Useful Tool for Self-Assessment and Rehabilitation of People with Multiple Sclerosis? A Systematic Review. Brain Sciences 2021;11(9):1187 View
  14. Creagh A, Dondelinger F, Lipsmeier F, Lindemann M, De Vos M. Longitudinal Trend Monitoring of Multiple Sclerosis Ambulation Using Smartphones. IEEE Open Journal of Engineering in Medicine and Biology 2022;3:202 View
  15. Gupta A. Digital Phenotyping in Clinical Neurology. Seminars in Neurology 2022;42(01):048 View
  16. Soulard J, Vaillant J, Baillet A, Gaudin P, Vuillerme N. Gait and Axial Spondyloarthritis: Comparative Gait Analysis Study Using Foot-Worn Inertial Sensors. JMIR mHealth and uHealth 2021;9(11):e27087 View
  17. . MindKind: A mixed-methods protocol for the feasibility of global digital mental health studies in young people. Wellcome Open Research 2021;6:275 View
  18. Salchow-Hömmen C, Skrobot M, Jochner M, Schauer T, Kühn A, Wenger N. Review—Emerging Portable Technologies for Gait Analysis in Neurological Disorders. Frontiers in Human Neuroscience 2022;16 View
  19. Pratap A, Homiar A, Waninger L, Herd C, Suver C, Volponi J, Anguera J, Areán P. Real-world behavioral dataset from two fully remote smartphone-based randomized clinical trials for depression. Scientific Data 2022;9(1) View
  20. van Oirschot P, Heerings M, Wendrich K, den Teuling B, Dorssers F, van Ee R, Martens M, Jongen P. A Two-Minute Walking Test With a Smartphone App for Persons With Multiple Sclerosis: Validation Study. JMIR Formative Research 2021;5(11):e29128 View
  21. Beukenhorst A, Burke K, Scheier Z, Miller T, Paganoni S, Keegan M, Collins E, Connaghan K, Tay A, Chan J, Berry J, Onnela J. Using Smartphones to Reduce Research Burden in a Neurodegenerative Population and Assessing Participant Adherence: A Randomized Clinical Trial and Two Observational Studies. JMIR mHealth and uHealth 2022;10(2):e31877 View
  22. van Beek J, Lehnick D, Pastore-Wapp M, Wapp S, Kamm C, Nef T, Vanbellingen T. Tablet app-based dexterity training in multiple sclerosis (TAD-MS): a randomized controlled trial. Disability and Rehabilitation: Assistive Technology 2022:1 View
  23. Rosenlund M, Kinnunen U, Saranto K. The Use of Digital Health Services Among Patients and Citizens Living at Home: Scoping Review. Journal of Medical Internet Research 2023;25:e44711 View
  24. Foong Y, Bridge F, Merlo D, Gresle M, Zhu C, Buzzard K, Butzkueven H, van der Walt A. Smartphone monitoring of cognition in people with multiple sclerosis: A systematic review. Multiple Sclerosis and Related Disorders 2023;73:104674 View
  25. Howard Z, Win K, Guan V. Mobile apps used for people living with multiple sclerosis: A scoping review. Multiple Sclerosis and Related Disorders 2023;73:104628 View
  26. Young F, Mason R, Morris R, Stuart S, Godfrey A. IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring. Sensors 2023;23(8):4100 View
  27. De Anda-Duran I, Hwang P, Popp Z, Low S, Ding H, Rahman S, Igwe A, Kolachalama V, Lin H, Au R. Matching science to reality: how to deploy a participant-driven digital brain health platform. Frontiers in Dementia 2023;2 View
  28. Taylor J, Heuer H, Clark A, Wise A, Manoochehri M, Forsberg L, Mester C, Rao M, Brushaber D, Kramer J, Welch A, Kornak J, Kremers W, Appleby B, Dickerson B, Domoto‐Reilly K, Fields J, Ghoshal N, Graff‐Radford N, Grossman M, Hall M, Huey E, Irwin D, Lapid M, Litvan I, Mackenzie I, Masdeu J, Mendez M, Nevler N, Onyike C, Pascual B, Pressman P, Rankin K, Ratnasiri B, Rojas J, Tartaglia M, Wong B, Gorno‐Tempini M, Boeve B, Rosen H, Boxer A, Staffaroni A. Feasibility and acceptability of remote smartphone cognitive testing in frontotemporal dementia research. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 2023;15(2) View

Books/Policy Documents

  1. Luxton R. Advanced Sensor Technology. View