Published on in Vol 21, No 8 (2019): August

Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study

Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study

Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study

Journals

  1. Ziemssen T, Kern R, Voigt I, Haase R. Data Collection in Multiple Sclerosis: The MSDS Approach. Frontiers in Neurology 2020;11 View
  2. Umbricht D, Cheng W, Lipsmeier F, Bamdadian A, Lindemann M. Deep Learning-Based Human Activity Recognition for Continuous Activity and Gesture Monitoring for Schizophrenia Patients With Negative Symptoms. Frontiers in Psychiatry 2020;11 View
  3. van Beek J, van Wegen E, Rietberg M, Nyffeler T, Bohlhalter S, Kamm C, Nef T, Vanbellingen T. Feasibility of a Home-Based Tablet App for Dexterity Training in Multiple Sclerosis: Usability Study. JMIR mHealth and uHealth 2020;8(6):e18204 View
  4. Block V, Bove R. We should monitor our patients with wearable technology instead of neurological examination – Yes. Multiple Sclerosis Journal 2020;26(9):1024 View
  5. Middleton R, Pearson O, Ingram G, Craig E, Rodgers W, Downing-Wood H, Hill J, Tuite-Dalton K, Roberts C, Watson L, Ford D, Nicholas R. A Rapid Electronic Cognitive Assessment Measure for Multiple Sclerosis: Validation of Cognitive Reaction, an Electronic Version of the Symbol Digit Modalities Test. Journal of Medical Internet Research 2020;22(9):e18234 View
  6. Matthews P, Block V, Leocani L. E-health and multiple sclerosis. Current Opinion in Neurology 2020;33(3):271 View
  7. Allen-Philbey K, Middleton R, Tuite-Dalton K, Baker E, Stennett A, Albor C, Schmierer K. Can We Improve the Monitoring of People With Multiple Sclerosis Using Simple Tools, Data Sharing, and Patient Engagement?. Frontiers in Neurology 2020;11 View
  8. Creagh A, Simillion C, Scotland A, Lipsmeier F, Bernasconi C, Belachew S, van Beek J, Baker M, Gossens C, Lindemann M, De Vos M. Smartphone-based remote assessment of upper extremity function for multiple sclerosis using the Draw a Shape Test. Physiological Measurement 2020;41(5):054002 View
  9. Gromisch E, Turner A, Haselkorn J, Lo A, Agresta T. Mobile health (mHealth) usage, barriers, and technological considerations in persons with multiple sclerosis: a literature review. JAMIA Open 2021;4(3) View
  10. Bourke A, Scotland A, Lipsmeier F, Gossens C, Lindemann M. Gait Characteristics Harvested during a Smartphone-Based Self-Administered 2-Minute Walk Test in People with Multiple Sclerosis: Test-Retest Reliability and Minimum Detectable Change. Sensors 2020;20(20):5906 View
  11. Torkildsen Ø, Linker R, Sesmero J, Fantaccini S, la Rosa R, Seze J, Duddy M, Chan A. Living With Secondary Progressive Multiple Sclerosis in Europe: Perspectives of Multiple Stakeholders. Neurodegenerative Disease Management 2021;11(1):9 View
  12. Schmalz O, Jacob C, Ammann J, Liss B, Iivanainen S, Kammermann M, Koivunen J, Klein A, Popescu R. Digital Monitoring and Management of Patients With Advanced or Metastatic Non-Small Cell Lung Cancer Treated With Cancer Immunotherapy and Its Impact on Quality of Clinical Care: Interview and Survey Study Among Health Care Professionals and Patients. Journal of Medical Internet Research 2020;22(12):e18655 View
  13. 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
  14. Pratap A, Grant D, Vegesna A, Tummalacherla M, Cohan S, Deshpande C, Mangravite L, Omberg L. 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. JMIR mHealth and uHealth 2020;8(10):e22108 View
  15. Cheng W, Bourke A, Lipsmeier F, Bernasconi C, Belachew S, Gossens C, Graves J, Montalban X, Lindemann M. U-turn speed is a valid and reliable smartphone-based measure of multiple sclerosis-related gait and balance impairment. Gait & Posture 2021;84:120 View
  16. Altmann P, Hinterberger W, Leutmezer F, Ponleitner M, Monschein T, Zrzavy T, Zulehner G, Kornek B, Lanzenberger R, Berek K, Rommer P, Berger T, Bsteh G. The Smartphone App haMSter for Tracking Patient-Reported Outcomes in People With Multiple Sclerosis: Protocol for a Pilot Study. JMIR Research Protocols 2021;10(5):e25011 View
  17. Creagh A, Simillion C, Bourke A, Scotland A, Lipsmeier F, Bernasconi C, van Beek J, Baker M, Gossens C, Lindemann M, De Vos M. Smartphone- and Smartwatch-Based Remote Characterisation of Ambulation in Multiple Sclerosis During the Two-Minute Walk Test. IEEE Journal of Biomedical and Health Informatics 2021;25(3):838 View
  18. BUOITE STELLA A, AJČEVIĆ M, FURLANIS G, CILLOTTO T, MENICHELLI A, ACCARDO A, MANGANOTTI P. Smart technology for physical activity and health assessment during COVID-19 lockdown. The Journal of Sports Medicine and Physical Fitness 2021;61(3) View
  19. 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
  20. 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
  21. Joshi M, Archer S, Morbi A, Arora S, Kwasnicki R, Ashrafian H, Khan S, Cooke G, Darzi A. Short-Term Wearable Sensors for In-Hospital Medical and Surgical Patients: Mixed Methods Analysis of Patient Perspectives. JMIR Perioperative Medicine 2021;4(1):e18836 View
  22. De Angelis M, Lavorgna L, Carotenuto A, Petruzzo M, Lanzillo R, Brescia Morra V, Moccia M. Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review. Journal of Clinical Medicine 2021;10(11):2328 View
  23. Scholz M, Haase R, Trentzsch K, Stölzer-Hutsch H, Ziemssen T. Improving Digital Patient Care: Lessons Learned from Patient-Reported and Expert-Reported Experience Measures for the Clinical Practice of Multidimensional Walking Assessment. Brain Sciences 2021;11(6):786 View
  24. Vandendriessche B, Godfrey A, Izmailova E. Multimodal biometric monitoring technologies drive the development of clinical assessments in the home environment. Maturitas 2021;151:41 View
  25. Creagh A, Lipsmeier F, Lindemann M, Vos M. Interpretable deep learning for the remote characterisation of ambulation in multiple sclerosis using smartphones. Scientific Reports 2021;11(1) View
  26. Montalban X, Graves J, Midaglia L, Mulero P, Julian L, Baker M, Schadrack J, Gossens C, Ganzetti M, Scotland A, Lipsmeier F, van Beek J, Bernasconi C, Belachew S, Lindemann M, Hauser S. A smartphone sensor-based digital outcome assessment of multiple sclerosis. Multiple Sclerosis Journal 2022;28(4):654 View
  27. Bove R, Bruce C, Lunders C, Pearce J, Liu J, Schleimer E, Hauser S, Stewart W, Jones J. Electronic Health Record Technology Designed for the Clinical Encounter. Neurology Clinical Practice 2021;11(4):318 View
  28. Ziemssen T, Bhan V, Chataway J, Chitnis T, Campbell Cree B, Havrdova E, Kappos L, Labauge P, Miller A, Nakahara J, Oreja-Guevara C, Palace J, Singer B, Trojano M, Patil A, Rauser B, Hach T. Secondary Progressive Multiple Sclerosis. Neurology Neuroimmunology & Neuroinflammation 2023;10(1) View
  29. Clay I, Cormack F, Fedor S, Foschini L, Gentile G, van Hoof C, Kumar P, Lipsmeier F, Sano A, Smarr B, Vandendriessche B, De Luca V. Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint. Journal of Medical Internet Research 2022;24(5):e35951 View
  30. Lyamina N, Kharytonov S. Digital wearable devices in cardiac rehabilitation: patient need and satisfaction. Literature Review. CardioSomatics 2022;13(1):23 View
  31. 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
  32. Guo G, Zhang H, Yao L, Li H, Xu C, Li Z, Xu W. MSLife. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2021;5(4):1 View
  33. Graves J, Ganzetti M, Dondelinger F, Lipsmeier F, Belachew S, Bernasconi C, Montalban X, van Beek J, Baker M, Gossens C, Lindemann M. Preliminary validity of the Draw a Shape Test for upper extremity assessment in multiple sclerosis. Annals of Clinical and Translational Neurology 2023;10(2):166 View
  34. 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
  35. 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
  36. Woelfle T, Pless S, Wiencierz A, Kappos L, Naegelin Y, Lorscheider J. Practice Effects of Mobile Tests of Cognition, Dexterity, and Mobility on Patients With Multiple Sclerosis: Data Analysis of a Smartphone-Based Observational Study. Journal of Medical Internet Research 2021;23(11):e30394 View
  37. 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
  38. Ali S, Selby D, Khalid K, Dempsey K, Mackey E, Small N, van der Veer S, Mcmillan B, Bower P, Brown B, McBeth J, Dixon W. Engagement with consumer smartwatches for tracking symptoms of individuals living with multiple long-term conditions (multimorbidity): A longitudinal observational study. Journal of Multimorbidity and Comorbidity 2021;11 View
  39. Masanneck L, Räuber S, Schroeter C, Lehnerer S, Ziemssen T, Ruck T, Meuth S, Pawlitzki M. Driving time-based identification of gaps in specialised care coverage: An example of neuroinflammatory diseases in Germany. DIGITAL HEALTH 2023;9 View
  40. van der Walt A, Butzkueven H, Shin R, Midaglia L, Capezzuto L, Lindemann M, Davies G, Butler L, Costantino C, Montalban X. Developing a Digital Solution for Remote Assessment in Multiple Sclerosis: From Concept to Software as a Medical Device. Brain Sciences 2021;11(9):1247 View
  41. 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
  42. Morgan A, Bégin D, Heisz J, Tang A, Thabane L, Richardson J. Measurement properties of remotely or self-administered physical performance measures to assess mobility: a systematic review protocol. Physical Therapy Reviews 2022;27(2):95 View
  43. Keogh A, Argent R, Anderson A, Caulfield B, Johnston W. Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review. Journal of NeuroEngineering and Rehabilitation 2021;18(1) View
  44. Masanneck L, Gieseler P, Gordon W, Meuth S, Stern A. Evidence from ClinicalTrials.gov on the growth of Digital Health Technologies in neurology trials. npj Digital Medicine 2023;6(1) View
  45. Goldsack J, Dowling A, Samuelson D, Patrick-Lake B, Clay I. Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint. Digital Biomarkers 2021;5(1):53 View
  46. Altmann P, Ponleitner M, Monschein T, Krajnc N, Zulehner G, Zrzavy T, Leutmezer F, Rommer P, Kornek B, Berger T, Bsteh G. Feasibility of a smartphone app to monitor patient reported outcomes in multiple sclerosis: The haMSter interventional trial. DIGITAL HEALTH 2022;8:205520762211353 View
  47. Huhn S, Matzke I, Koch M, Gunga H, Maggioni M, Sié A, Boudo V, Ouedraogo W, Compaoré G, Bunker A, Sauerborn R, Bärnighausen T, Barteit S. Using wearable devices to generate real-world, individual-level data in rural, low-resource contexts in Burkina Faso, Africa: A case study. Frontiers in Public Health 2022;10 View
  48. Messan K, Pham L, Harris T, Kim Y, Morgan V, Kosa P, Bielekova B. Assessment of Smartphone-Based Spiral Tracing in Multiple Sclerosis Reveals Intra-Individual Reproducibility as a Major Determinant of the Clinical Utility of the Digital Test. Frontiers in Medical Technology 2022;3 View
  49. Barrios L, Amon R, Oldrati P, Hilty M, Holz C, Lutterotti A. Cognitive fatigability assessment test (cFAST): Development of a new instrument to assess cognitive fatigability and pilot study on its association to perceived fatigue in multiple sclerosis. DIGITAL HEALTH 2022;8:205520762211177 View
  50. 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
  51. Hossain M, Daskalaki E, Brüstle A, Desborough J, Lueck C, Suominen H. The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review. BMC Medical Informatics and Decision Making 2022;22(1) View
  52. Ganzetti M, Graves J, Holm S, Dondelinger F, Midaglia L, Gaetano L, Craveiro L, Lipsmeier F, Bernasconi C, Montalban X, Hauser S, Lindemann M. Neural correlates of digital measures shown by structural MRI: a post-hoc analysis of a smartphone-based remote assessment feasibility study in multiple sclerosis. Journal of Neurology 2023;270(3):1624 View
  53. Katrine W, Ritzel S, Caroline K, Marie L, Olsgaard B, Lasse S. Potentials and barriers of using digital tools for collecting daily measurements in multiple sclerosis research. DIGITAL HEALTH 2021;7 View
  54. Sieber C, Haag C, Polhemus A, Sylvester R, Kool J, Gonzenbach R, von Wyl V. Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis. Frontiers in Digital Health 2023;5 View
  55. 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
  56. Colloud S, Metcalfe T, Askin S, Belachew S, Ammann J, Bos E, Kilchenmann T, Strijbos P, Eggenspieler D, Servais L, Garay C, Konstantakopoulos A, Ritzhaupt A, Vetter T, Vincenzi C, Cerreta F. Evolving regulatory perspectives on digital health technologies for medicinal product development. npj Digital Medicine 2023;6(1) View
  57. 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
  58. Graves J, Elantkowski M, Zhang Y, Dondelinger F, Lipsmeier F, Bernasconi C, Montalban X, Midaglia L, Lindemann M. Assessment of Upper Extremity Function in Multiple Sclerosis: Feasibility of a Digital Pinching Test. JMIR Formative Research 2023;7:e46521 View
  59. Dorsch E, Röhling H, Zocholl D, Hafermann L, Paul F, Schmitz-Hübsch T. Progression events defined by home-based assessment of motor function in multiple sclerosis: protocol of a prospective study. Frontiers in Neurology 2023;14 View
  60. 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
  61. 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
  62. Motolese F, Capone F, Magliozzi A, Vico C, Iaccarino G, Falato E, Pilato F, Di Lazzaro V. A smart devices based secondary prevention program for cerebrovascular disease patients. Frontiers in Neurology 2023;14 View
  63. 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
  64. Chén O, Lipsmeier F, Phan H, Dondelinger F, Creagh A, Gossens C, Lindemann M, de Vos M. Personalized Longitudinal Assessment of Multiple Sclerosis Using Smartphones. IEEE Journal of Biomedical and Health Informatics 2023;27(7):3633 View
  65. Tatum W, Acton E, Freund B, de la Cruz Gutierrez M, Feyissa A, Brigham T. Smartphone use in Neurology: a bibliometric analysis and visualization of things to come. Frontiers in Neurology 2023;14 View
  66. 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
  67. Vacchi L, Zirone E, Strina V, Cavaletti G, Ferrarese C. Mobile Applications to Support Multiple Sclerosis Communities: The Post-COVID-19 Scenario. Telemedicine and e-Health 2024;30(6):e1615 View
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  69. Sarnataro A, Cuomo N, Russo C, Carotenuto A, Lanzillo R, Moccia M, Petracca M, Morra V, Saccà F. Integration of the expanded disability status scale with ambulation, visual and cognitive tests. Neurological Sciences 2024;45(10):4799 View
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Books/Policy Documents

  1. Cancela J, Charlafti I, Colloud S, Wu C. Digital Health. View
  2. Lam J, Hasan M, Ahmed K, Hossain M. Recent Challenges in Intelligent Information and Database Systems. View