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

Design and Formative Evaluation of Mobile Apps (664) Ecological Momentary Assessment (EMA) (297) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317) Sleep Monitoring, Sleep Quality, Sleep Disorders (170) mHealth for Data Collection and Research (917) Usability of Apps and User Perceptions of mHealth (902) User-centred Design Case Studies (564) Human Factors and Usability Case Studies (748)

Published on in Vol 9, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16304, first published .
The SleepFit Tablet Application for Home-Based Clinical Data Collection in Parkinson Disease: User-Centric Development and Usability Study

The SleepFit Tablet Application for Home-Based Clinical Data Collection in Parkinson Disease: User-Centric Development and Usability Study

The SleepFit Tablet Application for Home-Based Clinical Data Collection in Parkinson Disease: User-Centric Development and Usability Study

Authors of this article:

Alessandro Mascheroni1 Author Orcid Image ;   Eun Kyoung Choe2 Author Orcid Image ;   Yuhan Luo2 Author Orcid Image ;   Michele Marazza3 Author Orcid Image ;   Clara Ferlito4 Author Orcid Image ;   Serena Caverzasio4 Author Orcid Image ;   Francesco Mezzanotte4 Author Orcid Image ;   Alain Kaelin-Lang4, 5, 6 Author Orcid Image ;   Francesca Faraci1 Author Orcid Image ;   Alessandro Puiatti1 Author Orcid Image ;   Pietro Luca Ratti4 Author Orcid Image
Article Authors Cited by (4) Tweetations (5) Metrics

Journals

  1. Raschellà F, Scafa S, Puiatti A, Martin Moraud E, Ratti P. Actigraphy Enables Home Screening of Rapid Eye Movement Behavior Disorder in Parkinson's Disease. Annals of Neurology 2023;93(2):317 View
  2. Gaßner H, Friedrich J, Masuch A, Jukic J, Stallforth S, Regensburger M, Marxreiter F, Winkler J, Klucken J. The Effects of an Individualized Smartphone-Based Exercise Program on Self-defined Motor Tasks in Parkinson Disease: Pilot Interventional Study. JMIR Rehabilitation and Assistive Technologies 2022;9(4):e38994 View
  3. 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
  4. Conte R, Sansone F, Tonacci A, Pala A. Privacy-by-Design and Minimization within a Small Electronic Health Record: The Health360 Case Study. Applied Sciences 2022;12(17):8441 View