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

Journals

  1. Hsieh K, Fanning J, Frechette M, Sosnoff J. Usability of a Fall Risk Mobile Health Application for People with Multiple Sclerosis: A Mixed Methods Study (Preprint). JMIR Human Factors 2020 View
  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
  5. Mokhberdezfuli M, Ayatollahi H, Naser Moghadasi A, Taiar R. A Smartphone-based Application for Self-Management in Multiple Sclerosis. Journal of Healthcare Engineering 2021;2021:1 View
  6. Freeman L, Kee A, Tian M, Mehta R. Retrospective Claims Analysis of Treatment Patterns, Relapse, Utilization, and Cost Among Patients with Multiple Sclerosis Initiating Second-Line Disease-Modifying Therapy. Drugs - Real World Outcomes 2021;8(4):497 View
  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 2024;19(3):889 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
  29. Pinarello C, Elmers J, Inojosa H, Beste C, Ziemssen T. Management of multiple sclerosis fatigue in the digital age: from assessment to treatment. Frontiers in Neuroscience 2023;17 View
  30. Woelfle T, Bourguignon L, Lorscheider J, Kappos L, Naegelin Y, Jutzeler C. Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective. Journal of Medical Internet Research 2023;25:e44428 View
  31. Daniore P, Nittas V, Gille F, von Wyl V. Promoting participation in remote digital health studies: An expert interview study. DIGITAL HEALTH 2023;9 View
  32. Nguyen T, Leow A, Ajilore O. A Review on Smartphone Keystroke Dynamics as a Digital Biomarker for Understanding Neurocognitive Functioning. Brain Sciences 2023;13(6):959 View
  33. Ferreira V, Metting E, Schauble J, Seddighi H, Beumeler L, Gallo V. eHealth tools to assess the neurological function for research, in absence of the neurologist – a systematic review, part I (software). Journal of Neurology 2024;271(1):211 View
  34. Lu Z, Signer T, Sylvester R, Gonzenbach R, von Wyl V, Haag C. Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals. JMIR mHealth and uHealth 2023;11:e50729 View
  35. Oh J, Capezzuto L, Kriara L, Schjodt-Eriksen J, van Beek J, Bernasconi C, Montalban X, Butzkueven H, Kappos L, Giovannoni G, Bove R, Julian L, Baker M, Gossens C, Lindemann M. Use of smartphone-based remote assessments of multiple sclerosis in Floodlight Open, a global, prospective, open-access study. Scientific Reports 2024;14(1) View
  36. Kummer B, Busis N. Beyond Audio-Video Telehealth: Perspective on the Current State and Future Directions of Digital Neurological Care in the United States. JMIR Neurotechnology 2024;3:e46736 View
  37. Creagh A, Hamy V, Yuan H, Mertes G, Tomlinson R, Chen W, Williams R, Llop C, Yee C, Duh M, Doherty A, Garcia-Gancedo L, Clifton D. Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis. npj Digital Medicine 2024;7(1) View
  38. Antonioni A, Baroni A, Milani G, Cordioli I, Straudi S. Role of Smartphone Applications in the Assessment and Management of Fatigue in Patients with Multiple Sclerosis: A Scoping Review. Sclerosis 2024;2(1):42 View
  39. Boma P, Kaponda A, Panda J, Bonnechère B. Enhancing the Management of Pediatric Sickle Cell Disease by Integrating Functional Evaluation to Mitigate the Burden of Vaso-Occlusive Crises. Journal of Vascular Diseases 2024;3(1):77 View
  40. Harris C, Tang Y, Birnbaum E, Cherian C, Mendhe D, Chen M. Digital Neuropsychology beyond Computerized Cognitive Assessment: Applications of Novel Digital Technologies. Archives of Clinical Neuropsychology 2024;39(3):290 View
  41. Chico-Garcia J, Sainz-Amo R, Monreal E, Rodriguez-Jorge F, Sainz de la Maza S, Masjuan J, Villar L, Costa-Frossard França L. Passive assessment of tapping speed through smartphone is useful for monitoring multiple sclerosis. Multiple Sclerosis and Related Disorders 2024;86:105595 View
  42. Sisodiya S, Gulcebi M, Fortunato F, Mills J, Haynes E, Bramon E, Chadwick P, Ciccarelli O, David A, De Meyer K, Fox N, Davan Wetton J, Koltzenburg M, Kullmann D, Kurian M, Manji H, Maslin M, Matharu M, Montgomery H, Romanello M, Werring D, Zhang L, Friston K, Hanna M. Climate change and disorders of the nervous system. The Lancet Neurology 2024;23(6):636 View
  43. Fu Y, Zhang Y, Ye B, Babineau J, Zhao Y, Gao Z, Mihailidis A. Smartphone-Based Hand Function Assessment: Systematic Review. Journal of Medical Internet Research 2024;26:e51564 View
  44. Webster D, Haberman R, Perez-Chada L, Tummalacherla M, Tediarjo A, Yadav V, Neto E, MacDuffie W, DePhillips M, Sieg E, Catron S, Grant C, Francis W, Nguyen M, Yussuff M, Castillo R, Yan D, Neimann A, Reddy S, Ogdie A, Kolivras A, Kellen M, Mangravite L, Sieberts S, Omberg L, Merola J, Scher J. Clinical Validation of Digitally Acquired Clinical Data and Machine Learning Models for Remote Measurement of Psoriasis and Psoriatic Arthritis: A Proof-of-Concept Study. The Journal of Rheumatology 2024;51(8):781 View
  45. Proietti T, Bandini A. Wearable Technologies for Monitoring Upper Extremity Functions During Daily Life in Neurologically Impaired Individuals. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2024;32:2737 View
  46. Chico-Garcia J, Sainz Amo R, Monreal E, Sainz de la Maza S, Rodriguez Jorge F, Masjuan J, Costa-Frossard L, Villar L. Progression independent of relapse activity can be predicted by passively acquired tapping speed through a smartphone for 1 month: A prospective study. Multiple Sclerosis Journal 2024;30(10):1341 View
  47. Scaramozza M, Ruet A, Chiesa P, Ahamada L, Bartholomé E, Carment L, Charre-Morin J, Cosne G, Diouf L, Guo C, Juraver A, Kanzler C, Karatsidis A, Mazzà C, Penalver-Andres J, Ruiz M, Saubusse A, Simoneau G, Scotland A, Sun Z, Tang M, van Beek J, Zajac L, Belachew S, Brochet B, Campbell N. Sensor-Derived Measures of Motor and Cognitive Functions in People With Multiple Sclerosis Using Unsupervised Smartphone-Based Assessments: Proof-of-Concept Study. JMIR Formative Research 2024;8:e60673 View
  48. Jin K, Kosa P, Bielekova B. Smartphone tests quantify lower extremities dysfunction in multiple sclerosis. Frontiers in Neurology 2024;15 View

Books/Policy Documents

  1. Luxton R. Advanced Sensor Technology. View