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

Non-randomized Protocols and Methods (ehealth) (672) Chronic Conditions (436) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1736) Wearable Devices and Sensors (1138) Cognitive and Neurorehabilitation (352) Neurology and Neurosciences (286)

Published on in Vol 14 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58612, first published .
Detecting Freezing of Gait in Parkinson Disease Using Multiple Wearable Sensors Sets During Various Walking Tasks Relative to Medication Conditions (DetectFoG): Protocol for a Prospective Cohort Study

Detecting Freezing of Gait in Parkinson Disease Using Multiple Wearable Sensors Sets During Various Walking Tasks Relative to Medication Conditions (DetectFoG): Protocol for a Prospective Cohort Study

Detecting Freezing of Gait in Parkinson Disease Using Multiple Wearable Sensors Sets During Various Walking Tasks Relative to Medication Conditions (DetectFoG): Protocol for a Prospective Cohort Study

Authors of this article:

Sébastien Cordillet1 Author Orcid Image ;   Sophie Drapier2 Author Orcid Image ;   Frédérique Leh2 Author Orcid Image ;   Audeline Dumont1 Author Orcid Image ;   Florian Bidet1 Author Orcid Image ;   Isabelle Bonan1 Author Orcid Image ;   Karim Jamal1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Rojek I, Mikołajewska E, Małolepsza O, Kozielski M, Mikołajewski D. Comparative Analysis of Different AI Approaches to Stroke Patients’ Gait Analysis. Applied Sciences 2025;15(20):10896 View

Conference Proceedings

  1. Nagarathna P, Fallahhusein M, Mishra A, Saravanan T, Kavitha R. 2025 International Conference on Intelligent Computing and Knowledge Extraction (ICICKE). Early Detection of Parkinson’s Disease using Wearable Sensor-based Gait analysis with Logistic Regression View