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

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1396) Registered Report (560) Sensors at Home and Domotics (57) Ecological Momentary Assessment (EMA) (309)

Published on in Vol 8, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16414, first published .
Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial

Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial

Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial

Authors of this article:

Dimitris Gatsios1, 2 Author Orcid Image ;   Angelo Antonini3, 4 Author Orcid Image ;   Giovanni Gentile3, 4 Author Orcid Image ;   Andrea Marcante4 Author Orcid Image ;   Clelia Pellicano5 Author Orcid Image ;   Lucia Macchiusi5 Author Orcid Image ;   Francesca Assogna5 Author Orcid Image ;   Gianfranco Spalletta5 Author Orcid Image ;   Heather Gage6 Author Orcid Image ;   Morro Touray6 Author Orcid Image ;   Lada Timotijevic7 Author Orcid Image ;   Charo Hodgkins7 Author Orcid Image ;   Maria Chondrogiorgi1 Author Orcid Image ;   George Rigas2 Author Orcid Image ;   Dimitrios I Fotiadis2, 8 Author Orcid Image ;   Spyridon Konitsiotis1 Author Orcid Image
Article Authors Cited by (33) Tweetations (4) Metrics

Journals

  1. Carraro U, Albertin G, Martini A, Giuriati W, Guidolin D, Masiero S, Kern H, Hofer C, Marcante A, Ravara B. To contrast and reverse skeletal muscle weakness by Full-Body In-Bed Gym in chronic COVID-19 pandemic syndrome. European Journal of Translational Myology 2021 View
  2. Carraro U, Albertin G, Martini A, Giuriati W, Guidolin D, Masiero S, Kern H, Hofer C, Marcante A, Ravara B. To contrast and reverse skeletal muscle weakness by Full-Body In-Bed Gym in chronic COVID-19 pandemic syndrome. European Journal of Translational Myology 2021 View
  3. van den Bergh R, Bloem B, Meinders M, Evers L. The state of telemedicine for persons with Parkinson's disease. Current Opinion in Neurology 2021;34(4):589 View
  4. Wijers A, Hochstenbach L, Tissingh G. Telemonitoring via Questionnaires Reduces Outpatient Healthcare Consumption in Parkinson's Disease. Movement Disorders Clinical Practice 2021;8(7):1075 View
  5. Bouça-Machado R, Pona-Ferreira F, Leitão M, Clemente A, Vila-Viçosa D, Kauppila L, Costa R, Matias R, Ferreira J. Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease. Sensors 2021;21(15):4972 View
  6. van Wamelen D, Sringean J, Trivedi D, Carroll C, Schrag A, Odin P, Antonini A, Bloem B, Bhidayasiri R, Chaudhuri K. Digital health technology for non-motor symptoms in people with Parkinson's disease: Futile or future?. Parkinsonism & Related Disorders 2021;89:186 View
  7. Wasmann J, Pragt L, Eikelboom R, Swanepoel D. Digital Approaches to Automated and Machine Learning Assessments of Hearing: Scoping Review. Journal of Medical Internet Research 2022;24(2):e32581 View
  8. Morgan C, Tonkin E, Craddock I, Whone A. Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative Study. JMIR Human Factors 2022;9(3):e36370 View
  9. Özden F. The effect of mobile application-based rehabilitation in patients with Parkinson’s disease: A systematic review and meta-analysis. Clinical Neurology and Neurosurgery 2023;225:107579 View
  10. Xu Z, Shen B, Tang Y, Wu J, Wang J. Deep Clinical Phenotyping of Parkinson’s Disease: Towards a New Era of Research and Clinical Care. Phenomics 2022;2(5):349 View
  11. Hadley A, Riley D, Heldman D. Real-World Evidence for a Smartwatch-Based Parkinson’s Motor Assessment App for Patients Undergoing Therapy Changes. Digital Biomarkers 2021;5(3):206 View
  12. Chandrabhatla A, Pomeraniec I, Ksendzovsky A. Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson’s disease motor symptoms. npj Digital Medicine 2022;5(1) View
  13. Zhang Z, Chen J. The Enterprise's Willingness to Use Remote Monitoring Technology Under the Background of Green Operation and Service-Oriented Manufacturing. Journal of Organizational and End User Computing 2023;35(2):1 View
  14. Bendig J, Wolf A, Mark T, Frank A, Mathiebe J, Scheibe M, Müller G, Stahr M, Schmitt J, Reichmann H, Loewenbrück K, Falkenburger B. Feasibility of a Multimodal Telemedical Intervention for Patients with Parkinson’s Disease—A Pilot Study. Journal of Clinical Medicine 2022;11(4):1074 View
  15. Lee J, Yeom I, Chung M, Kim Y, Yoo S, Kim E. Use of Mobile Apps for Self-care in People With Parkinson Disease: Systematic Review. JMIR mHealth and uHealth 2022;10(1):e33944 View
  16. Godkin F, Turner E, Demnati Y, Vert A, Roberts A, Swartz R, McLaughlin P, Weber K, Thai V, Beyer K, Cornish B, Abrahao A, Black S, Masellis M, Zinman L, Beaton D, Binns M, Chau V, Kwan D, Lim A, Munoz D, Strother S, Sunderland K, Tan B, McIlroy W, Van Ooteghem K. Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease. Journal of Neurology 2022;269(5):2673 View
  17. Bendig J, Spanz A, Leidig J, Frank A, Stahr M, Reichmann H, Loewenbrück K, Falkenburger B. Measuring the Usability of eHealth Solutions for Patients With Parkinson Disease: Observational Study. JMIR Formative Research 2022;6(10):e39954 View
  18. Oyama G, Burq M, Hatano T, Marks W, Kapur R, Fernandez J, Fujikawa K, Furusawa Y, Nakatome K, Rainaldi E, Chen C, Ho K, Ogawa T, Kamo H, Oji Y, Takeshige-Amano H, Taniguchi D, Nakamura R, Sasaki F, Ueno S, Shiina K, Hattori A, Nishikawa N, Ishiguro M, Saiki S, Hayashi A, Motohashi M, Hattori N. Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan. Scientific Reports 2023;13(1) View
  19. Kanellos F, Tsamis K, Rigas G, Simos Y, Katsenos A, Kartsakalis G, Fotiadis D, Vezyraki P, Peschos D, Konitsiotis S. Clinical Evaluation in Parkinson’s Disease: Is the Golden Standard Shiny Enough?. Sensors 2023;23(8):3807 View
  20. Tsakanikas V, Ntanis A, Rigas G, Androutsos C, Boucharas D, Tachos N, Skaramagkas V, Chatzaki C, Kefalopoulou Z, Tsiknakis M, Fotiadis D. Evaluating Gait Impairment in Parkinson’s Disease from Instrumented Insole and IMU Sensor Data. Sensors 2023;23(8):3902 View
  21. Broeder S, Roussos G, De Vleeschhauwer J, D’Cruz N, de Xivry J, Nieuwboer A. A smartphone-based tapping task as a marker of medication response in Parkinson’s disease: a proof of concept study. Journal of Neural Transmission 2023;130(7):937 View
  22. Moreau C, Rouaud T, Grabli D, Benatru I, Remy P, Marques A, Drapier S, Mariani L, Roze E, Devos D, Dupont G, Bereau M, Fabbri M. Overview on wearable sensors for the management of Parkinson’s disease. npj Parkinson's Disease 2023;9(1) View
  23. Ravara B, Giuriati W, Maccarone M, Kern H, Masiero S, Carraro U. Optimized progression of Full-Body In-Bed Gym workout: an educational case report. European Journal of Translational Myology 2023;33(2) View
  24. Willemse I, Schootemeijer S, van den Bergh R, Dawes H, Nonnekes J, van de Warrenburg B. Smartphone applications for Movement Disorders: Towards collaboration and re-use. Parkinsonism & Related Disorders 2024;120:105988 View
  25. Minaei-Moghadam S, Manzari Z, Vaghee S, Mirhosseini S. Effectiveness of a supportive care program via a smartphone application on the quality of life and care burden among family caregivers of patients with major depressive disorder: a randomized controlled trial. BMC Public Health 2024;24(1) View
  26. Lee J, Suh Y, Kim E, Yoo S, Kim Y. A Mobile App for Comprehensive Symptom Management in People With Parkinson’s Disease. CIN: Computers, Informatics, Nursing 2024 View
  27. Zhang Y, Zeng Z, Mirian M, Yen K, Park K, Doo M, Ji J, Shen Z, McKeown M. Investigating the efficacy and importance of mobile-based assessments for Parkinson's disease: uncovering the potential of novel digital tests. Scientific Reports 2024;14(1) View
  28. Islam T, Washington P. Non-Invasive Biosensing for Healthcare Using Artificial Intelligence: A Semi-Systematic Review. Biosensors 2024;14(4):183 View
  29. Bhidayasiri R, Udomsirithamrong O, de Leon A, Maetzler W, Pilotto A. Empowering the management of early-onset Parkinson’s disease: The role of technology. Parkinsonism & Related Disorders 2024:107052 View
  30. Sapienza S, Tsurkalenko O, Giraitis M, Mejia A, Zelimkhanov G, Schwaninger I, Klucken J. Assessing the clinical utility of inertial sensors for home monitoring in Parkinson’s disease: a comprehensive review. npj Parkinson's Disease 2024;10(1) View

Books/Policy Documents

  1. Corzani M. Internet of Things for Human-Centered Design. View
  2. Alor-Hernández G, Sánchez-Morales L, García-Dimas F, Cruz-Ramos N, Sánchez-Cervantes J. Artificial Intelligence in Prescriptive Analytics. View