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
.
Journals
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- . MindKind: A mixed-methods protocol for the feasibility of global digital mental health studies in young people. Wellcome Open Research 2022;6:275 View
- 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
- 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
- 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
- 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
- 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
- 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
- Gupta A. Digital Phenotyping in Clinical Neurology. Seminars in Neurology 2022;42(01):048 View
- 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
- . MindKind: A mixed-methods protocol for the feasibility of global digital mental health studies in young people. Wellcome Open Research 2021;6:275 View
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Jin K, Kosa P, Bielekova B. Smartphone tests quantify lower extremities dysfunction in multiple sclerosis. Frontiers in Neurology 2024;15 View
Books/Policy Documents
- Luxton R. Advanced Sensor Technology. View