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

Wearable Devices and Sensors (888) Chatbots and Conversational Agents (531) Machine Learning (1465) Innovations and Technology for Physical Activity Education (742) Fitness Trackers and Smart Pedometers/Accelerometers (561) Usability of Apps and User Perceptions of mHealth (974) mHealth for Wellness, Behavior Change and Prevention (2871) Human Factors and Usability Case Studies (787)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28577, first published .
Feasibility, Usability, and Effectiveness of a Machine Learning–Based Physical Activity Chatbot: Quasi-Experimental Study

Feasibility, Usability, and Effectiveness of a Machine Learning–Based Physical Activity Chatbot: Quasi-Experimental Study

Feasibility, Usability, and Effectiveness of a Machine Learning–Based Physical Activity Chatbot: Quasi-Experimental Study

Authors of this article:

Quyen G To1 Author Orcid Image ;   Chelsea Green1 Author Orcid Image ;   Corneel Vandelanotte1 Author Orcid Image
Article Authors Cited by (25) Tweetations (11) Metrics

Quyen G To   1 , PhD ;   Chelsea Green   1 , BSc ;   Corneel Vandelanotte   1 , PhD

1 Physical Activity Research Group, Appleton Institute, Central Queensland University, Rockhampton, Australia

Corresponding Author:

  • Quyen G To, PhD
  • Physical Activity Research Group
  • Appleton Institute
  • Central Queensland University
  • 554-700 Yaamba Rd, Norman Gardens
  • Rockhampton, 4701
  • Australia
  • Phone: 61 7 4930 6456
  • Email: q.to@cqu.edu.au