Published on in Vol 8 , No 4 (2020) :Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19968, first published .
Effects of a Personalized Fitness Recommender System Using Gamification and Continuous Player Modeling: System Design and Long-Term Validation Study

Effects of a Personalized Fitness Recommender System Using Gamification and Continuous Player Modeling: System Design and Long-Term Validation Study

Effects of a Personalized Fitness Recommender System Using Gamification and Continuous Player Modeling: System Design and Long-Term Validation Study

Authors of this article:

Zhao Zhao 1 Author Orcid Image ;   Ali Arya 2 Author Orcid Image ;   Rita Orji 3 Author Orcid Image ;   Gerry Chan 2 Author Orcid Image

Journals

  1. Carlier S, Naessens V, De Backere F, De Turck F. A Software Engineering Framework for Reusable Design of Personalized Serious Games for Health: Development Study. JMIR Serious Games 2023;11:e40054 View
  2. Islam M, Lee S, Harden S, Lim S. Effects of vibrotactile feedback on yoga practice. Frontiers in Sports and Active Living 2022;4 View
  3. Zappatore M, Longo A, Martella A, Di Martino B, Esposito A, Gracco S. Semantic models for IoT sensing to infer environment–wellness relationships. Future Generation Computer Systems 2023;140:1 View
  4. Sun Y, Zhou J, Ji M, Pei L, Wang Z. Development and Evaluation of Health Recommender Systems: Systematic Scoping Review and Evidence Mapping. Journal of Medical Internet Research 2023;25:e38184 View
  5. Islas-Cota E, Gutierrez-Garcia J, Acosta C, Rodríguez L. A systematic review of intelligent assistants. Future Generation Computer Systems 2022;128:45 View
  6. Xu L, Shi H, Shen M, Ni Y, Zhang X, Pang Y, Yu T, Lian X, Yu T, Yang X, Li F. The Effects of mHealth-Based Gamification Interventions on Participation in Physical Activity: Systematic Review. JMIR mHealth and uHealth 2022;10(2):e27794 View
  7. Liu X, Gao B, Suleiman B, You H, Ma Z, Liu Y, Anaissi A. Privacy-Preserving Personalized Fitness Recommender System ( P 3 FitRec ) : A Multi-level Deep Learning Approach. ACM Transactions on Knowledge Discovery from Data 2023 View
  8. Izountar Y, Benbelkacem S, Otmane S, Khababa A, Masmoudi M, Zenati N. VR-PEER: A Personalized Exer-Game Platform Based on Emotion Recognition. Electronics 2022;11(3):455 View
  9. Venkatachalam P, Ray S. How do context-aware artificial intelligence algorithms used in fitness recommender systems? A literature review and research agenda. International Journal of Information Management Data Insights 2022;2(2):100139 View
  10. Chaudhari S, Ghanvatkar S, Kankanhalli A. Personalization of Intervention Timing for Physical Activity: Scoping Review. JMIR mHealth and uHealth 2022;10(2):e31327 View

Books/Policy Documents

  1. Ulmer T, Baldauf M. Human-Computer Interaction. User Experience and Behavior. View
  2. Torres-Toukoumidis A, Vintimilla-León D, De-Santis A, Cárdenas-Tapia J, Mäeots M. Communication and Applied Technologies. View