Published on in Vol 9, No 2 (2021): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25771, first published .
User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study

User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study

User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study

Authors of this article:

Ali Darzi1 Author Orcid Image ;   Sean M McCrea2 Author Orcid Image ;   Domen Novak1 Author Orcid Image

Journals

  1. Li X, Zeng H, Zhang J, Song A. Engagement Enhancement Based on Bayesian Optimization for Adaptive Assist-as-Needed Controller. IEEE Robotics and Automation Letters 2022;7(1):49 View
  2. Segundo Díaz R, Rovelo Ruiz G, Bouzouita M, Coninx K. Building blocks for creating enjoyable games—A systematic literature review. International Journal of Human-Computer Studies 2022;159:102758 View
  3. Paraschos P, Koulouriotis D. Game Difficulty Adaptation and Experience Personalization: A Literature Review. International Journal of Human–Computer Interaction 2023;39(1):1 View
  4. Novak V, Hass D, Hossain M, Sowers A, Clapp J. Effects of adaptation accuracy and magnitude in affect-aware difficulty adaptation for the multi-attribute task battery. International Journal of Human-Computer Studies 2024;183:103180 View
  5. Croissant M, Schofield G, McCall C. Theories, methodologies, and effects of affect-adaptive games: A systematic review. Entertainment Computing 2023;47:100591 View
  6. Xinru W. A novel jigsaw game with eye‐tracking: A multimodel interaction based on psycholinguistics for ADHD therapeutic. Computer Animation and Virtual Worlds 2024;35(1) View
  7. Ajani O, Mallipeddi R. Pareto-based Dynamic Difficulty Adjustment of a competitive exergame for arm rehabilitation. International Journal of Human-Computer Studies 2023;178:103100 View
  8. Chatterjee I, Goršič M, Hossain M, Clapp J, Novak V. Automated Classification of Dyadic Conversation Scenarios Using Autonomic Nervous System Responses. IEEE Transactions on Affective Computing 2023;14(4):3388 View
  9. da Silveira A, Lima de Souza M, Ghinea G, Saibel Santos C. Physiological Data for User Experience and Quality of Experience: A Systematic Review (2018–2022). International Journal of Human–Computer Interaction 2024:1 View
  10. Guo Z, Thawonmas R, Ren X. Rethinking dynamic difficulty adjustment for video game design. Entertainment Computing 2024;50:100663 View
  11. Guzmán D, Rengifo C, Guzmán J, Garcia Cena C. Virtual reality games for cognitive rehabilitation of older adults: a review of adaptive games, domains and techniques. Virtual Reality 2024;28(2) View
  12. Fisher N, Kulshreshth A. Exploring Dynamic Difficulty Adjustment Methods for Video Games. Virtual Worlds 2024;3(2):230 View
  13. Annisa Damastuti F, Firmansyah K, Miftachul Arif Y, Dutono T, Barakbah A, Hariadi M. Dynamic Level of Difficulties Using Q-Learning and Fuzzy Logic. IEEE Access 2024;12:137775 View
  14. Croissant M, Frister M, Schofield G, McCall C. Advancing Methodological Approaches in Affect-Adaptive Video Game Design: Empirical Validation of Emotion-Driven Gameplay Modification. International Journal of Human–Computer Interaction 2024:1 View
  15. Li X, Xia Y, Gursesli M, You X, Chen S, Thawonmas R. Enhancing Player Experience in a First-Person Shooter with Dynamic Audio Cue Adjustment Based on Gaussian Progress Regression. Applied Sciences 2024;14(23):11146 View

Books/Policy Documents

  1. Novak V, Koenig A, Riener R. Neurorehabilitation Technology. View
  2. Borawska A, Mateja A. Advances in Information Systems Development. View