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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Dynamic Difficulty Adjustment in Virtual Reality Exergames through Experience-driven Procedural Content Generation
Tobias Huber, Silvan Mertes, Stanislava Rangelova, et al.
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2021), pp. 1-8
Open Access | Times Cited: 22

Showing 22 citing articles:

When XR and AI Meet - A Scoping Review on Extended Reality and Artificial Intelligence
Teresa Hirzle, Florian Müller, Fiona Draxler, et al.
(2023), pp. 1-45
Open Access | Times Cited: 25
Born to Run, Programmed to Play: Mapping the Extended Reality Exergames Landscape
Sukran Karaosmanoglu, Sebastian Cmentowski, Lennart E. Nacke, et al.
(2024), pp. 1-28
Open Access | Times Cited: 8
LightSword: A Customized Virtual Reality Exergame for Long-Term Cognitive Inhibition Training in Older Adults
Qiuxin Du, Zhen Song, Haiyan Jiang, et al.
(2024), pp. 1-17
Open Access | Times Cited: 4
Angry Birds Level Generation to Achieve Diverse Results Having Controllable Similarity to an Example
Mury F. Dewantoro, Febri Abdullah, Ruck Thawonmas
Journal of Information Processing (2025) Vol. 33, pp. 210-218
Open Access
A Review of Dynamic Difficulty Adjustment Methods for Serious Games
Júlio Castro Lopes, Rui Pedro Lopes
Communications in computer and information science (2022), pp. 144-159
Closed Access | Times Cited: 14
Exploring Dynamic Difficulty Adjustment Methods for Video Games
Nicholas P. Fisher, Arun K. Kulshreshth
Virtual Worlds (2024) Vol. 3, Iss. 2, pp. 230-255
Open Access | Times Cited: 2
Stress Level Estimation Based on Physiological Signals for Virtual Reality Applications
Carmen Elisa Orozco-Mora, Daniela Oceguera‐Cuevas, Rita Q. Fuentes‐Aguilar, et al.
IEEE Access (2022) Vol. 10, pp. 68755-68767
Open Access | Times Cited: 11
Dynamic Level of Difficulties Using Q-Learning and Fuzzy Logic
Fardani Annisa Damastuti, Kenan Firmansyah, Yunifa Miftachul Arif, et al.
IEEE Access (2024) Vol. 12, pp. 137775-137789
Open Access | Times Cited: 1
Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview
Annette Brons, Shihan Wang, Bart Visser, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e47774-e47774
Open Access | Times Cited: 1
Force Feedback-Based Gamification: Performance Validation of Squat Exergame Using Pneumatic Gel Muscles and Dynamic Difficulty Adjustment
Priyanka Ramasamy, Gunarajulu Renganathan, Yuichi Kurita
IEEE Robotics and Automation Letters (2023) Vol. 8, Iss. 10, pp. 6371-6378
Closed Access | Times Cited: 2
Analyzing Exergame Recordings with Embedded Bio-Data in Immersive Virtual Reality
Pauline Bimberg, Marvin Minuth, Daniel Zielasko, et al.
2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) (2024), pp. 138-144
Closed Access
Solution Path Heuristics for Predicting Difficulty and Enjoyment Ratings of Roguelike Level Segments
Colan F. Biemer, Seth Cooper
(2024), pp. 1-8
Closed Access
Towards physiological detection of a “just-right” challenge level for motor learning in immersive virtual reality: a pilot study protocol. (Preprint)
Samory Houzangbe, Martin Lemay, Danielle Levac
JMIR Research Protocols (2024) Vol. 13, pp. e55730-e55730
Open Access
Exploring Emotional Responses with Dynamic Difficulty Adjustment Adaptation in Immersive Virtual Reality Exergaming
Renzhi Han, Boon Giin Lee, Dave Towey, et al.
2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC) (2024), pp. 621-627
Closed Access
Dynamic difficulty adjustment using deep reinforcement learning: A review
Tianyi Zheng
Applied and Computational Engineering (2024) Vol. 71, Iss. 1, pp. 157-162
Open Access
Dynamic Difficulty Adjustment in Virtual Reality Exergaming to Regulate Exertion Levels via Heart Rate Monitoring
Lucas Küntzer, M. Scherer, Tilo Mentler, et al.
(2024) Vol. 202, pp. 1-2
Closed Access
Does Where You Exercise Matter? The Influence of VR Environmental Cues and Social Cues on Exercise Motivation and Behavior
Jih‐Hsuan Tammy Lin, Christine Cook, Ji-Wei Yang
International Journal of Human-Computer Interaction (2024), pp. 1-17
Closed Access
Persona-driven Dominant/Submissive Map (PDSM) Generation for Tutorials
Michael Cerny Green, Ahmed Khalifa, Charity, et al.
(2022), pp. 1-10
Open Access | Times Cited: 1
Dynamic Difficulty Adjustment of Serious-Game Based on Synthetic Fog using Activity Theory Model
Fresy Nugroho, Puspa Miladin Nuraida Safitri Abdul Basid, Firma Sahrul Bahtiar, et al.
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 6
Open Access
A statistical approach to select the manipulated variables of a difficulty adjustment closed-loop control for an augmented reality video game
R. Campo, Gilber Andres Villaquiran, Carlos Felipe Rengifo Rodas, et al.
2019 IEEE 4th Colombian Conference on Automatic Control (CCAC) (2023), pp. 1-5
Closed Access
Towards physiological detection of a “just-right” challenge level for motor learning in immersive virtual reality: a pilot study. (Preprint)
Samory Houzangbe, Martin Lemay, Danielle Levac
(2023)
Closed Access
Machine Learning Methods to Personalize Persuasive Strategies in mHealth Interventions That Promote Physical Activity: Scoping Review and Categorization Overview (Preprint)
Annette Brons, Shihan Wang, Bart Visser, et al.
(2023)
Closed Access
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