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

Digital Health Reviews (1540) Web-based and Mobile Health Interventions (3661) mHealth for Wellness, Behavior Change and Prevention (3115) Innovations and Technology for Physical Activity Education (826) Artificial Intelligence (1762)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47774, first published .
Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview

Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview

Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview

Authors of this article:

Annette Brons1, 2, 3 Author Orcid Image ;   Shihan Wang2 Author Orcid Image ;   Bart Visser3 Author Orcid Image ;   Ben Kröse1, 4 Author Orcid Image ;   Sander Bakkes2 Author Orcid Image ;   Remco Veltkamp2 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Smiley A, Finkelstein J. Dynamic Prediction of Physical Exertion: Leveraging AI Models and Wearable Sensor Data During Cycling Exercise. Diagnostics 2024;15(1):52 View
  2. Garofano M, Del Sorbo R, Calabrese M, Giordano M, Di Palo M, Bartolomeo M, Ragusa C, Ungaro G, Fimiani G, Di Spirito F, Amato M, Ciccarelli M, Pascarelli C, Scanniello G, Bramanti P, Bramanti A. Remote Rehabilitation and Virtual Reality Interventions Using Motion Sensors for Chronic Low Back Pain: A Systematic Review of Biomechanical, Pain, Quality of Life, and Adherence Outcomes. Technologies 2025;13(5):186 View