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

Human Factors and Usability Case Studies (1023) Chronic Conditions (450) Neurology and Neurosciences (292) Focus Groups and Qualitative Research for Human Factors Research (1251) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1765) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (653) Co-Design & Participatory Design (179)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67986, first published .
Insights From a Mixed Methods Analysis of 3 Health Technologies Used in Patients With Parkinson Disease: Mixed Methods Study

Insights From a Mixed Methods Analysis of 3 Health Technologies Used in Patients With Parkinson Disease: Mixed Methods Study

Insights From a Mixed Methods Analysis of 3 Health Technologies Used in Patients With Parkinson Disease: Mixed Methods Study

Authors of this article:

Daniel Pérez-Rangel1 Author Orcid Image ;   Mariana H G Monje2 Author Orcid Image ;   Sylvie Grosjean3 Author Orcid Image ;   Martin Srp4 Author Orcid Image ;   Laura Antunes5 Author Orcid Image ;   Raquel Bouça-Machado5 Author Orcid Image ;   Ricardo Cacho5 Author Orcid Image ;   Sergio Domínguez Rodríguez6 Author Orcid Image ;   John Inocentes7 Author Orcid Image ;   Timothy Lynch7 Author Orcid Image ;   Argyri Tsakanika8 Author Orcid Image ;   Dimitrios Fotiadis8 Author Orcid Image ;   George Rigas8 Author Orcid Image ;   Evžen Růžička4 Author Orcid Image ;   Joaquim J Ferreira5 Author Orcid Image ;   Angelo Antonini9 Author Orcid Image ;   Norberto Malpica6 Author Orcid Image ;   Tiago Mestre10 Author Orcid Image ;   Álvaro Sánchez-Ferro1 Author Orcid Image ;   iCARE-PD Consortium
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Journals

  1. Zhao M, Liu R, Jin S, Ren B, Zhang Q. From data to diagnosis: A comprehensive review of machine learning-driven wearable sensors in healthcare. Bioelectrochemistry 2026;170:109228 View