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

Development and Evaluation of Research Methods, Instruments and Tools (490) mHealth for Data Collection and Research (956) Wearable Devices and Sensors (891) Mobile Health (mhealth) (2952)

Published on in Vol 6, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31775, first published .
Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study

Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study

Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study

Authors of this article:

Ghobad Maleki1, 2 Author Orcid Image ;   Ahnjili Zhuparris1, 2 Author Orcid Image ;   Ingrid Koopmans1 Author Orcid Image ;   Robert J Doll1 Author Orcid Image ;   Nicoline Voet3, 4 Author Orcid Image ;   Adam Cohen1 Author Orcid Image ;   Emilie van Brummelen1 Author Orcid Image ;   Geert Jan Groeneveld1, 2 Author Orcid Image ;   Joris De Maeyer5 Author Orcid Image
Article Authors Cited by (7) Tweetations (2) Metrics

Journals

  1. Zhuparris A, Maleki G, Koopmans I, Doll R, Voet N, Kraaij W, Cohen A, van Brummelen E, De Maeyer J, Groeneveld G. Smartphone and Wearable Sensors for the Estimation of Facioscapulohumeral Muscular Dystrophy Disease Severity: Cross-sectional Study. JMIR Formative Research 2023;7:e41178 View
  2. ZhuParris A, de Goede A, Yocarini I, Kraaij W, Groeneveld G, Doll R. Machine Learning Techniques for Developing Remotely Monitored Central Nervous System Biomarkers Using Wearable Sensors: A Narrative Literature Review. Sensors 2023;23(11):5243 View
  3. Zhuparris A, Maleki G, van Londen L, Koopmans I, Aalten V, Yocarini I, Exadaktylos V, van Hemert A, Cohen A, Gal P, Doll R, Groeneveld G, Jacobs G, Kraaij W. A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity. Scientific Reports 2023;13(1) View
  4. Poleur M, Markati T, Servais L. The use of digital outcome measures in clinical trials in rare neurological diseases: a systematic literature review. Orphanet Journal of Rare Diseases 2023;18(1) View
  5. Bibbo D, De Marchis C, Schmid M, Ranaldi S. Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review. Physiological Measurement 2023;44(12):12TR01 View
  6. Zubair A. Utilization of wearable technology to track functional changes in a patient with myopathy. Brain Circulation 2024;10(2):190 View
  7. Megalizzi D, Trastulli G, Colantoni L, Proietti Piorgo E, Primiano G, Sancricca C, Caltagirone C, Cascella R, Strafella C, Giardina E. Deciphering the Complexity of FSHD: A Multimodal Approach as a Model for Rare Disorders. International Journal of Molecular Sciences 2024;25(20):10949 View