ChallengeDetect: Investigating the Potential of Detecting In-Game Challenge Experience from Physiological Measures-Reference-Cited by-同舟云学术

ChallengeDetect: Investigating the Potential of Detecting In-Game Challenge Experience from Physiological Measures

Published:2023-04-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
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Author:

Peng Xiaolan¹^ORCID,Xie Xurong²^ORCID,Huang Jin³^ORCID,Jiang Chutian⁴^ORCID,Wang Haonian⁵^ORCID,Denisova Alena⁶^ORCID,Chen Hui⁷^ORCID,Tian Feng³^ORCID,Wang Hongan⁷^ORCID

Affiliation:

1. Institute of software,Chinese Academy of Sciences, China

2. Institute of Software, Chinese Academy of Science, China

3. Institute of software, Chinese Academy of Sciences, China

4. The Hong Kong University of Science and Technology (Guangzhou), Computational Media and Arts Thrust, China and Institute of Software, Chinese Academy of Sciences, China

5. Beijing Normal University, Department of Artificial Intelligence, China

6. Department of Computer Science, University of York, United Kingdom

7. Beijing Key Lab of Human-Computer Interactions, Institute of Software, Chinese Academy of Sciences, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3544548.3581232

Reference69 articles.

1. Ernest Adams. 2014. Fundamentals of game design. Pearson Education. Ernest Adams. 2014. Fundamentals of game design. Pearson Education.

2. Challenge-Sensitive Action Selection: an Application to Game Balancing

3. Electroencephalogram and Physiological Signal Analysis for Assessing Flow in Games

4. Christopher M Bishop and Nasser M Nasrabadi . 2006. Pattern recognition and machine learning. Vol. 4 . Springer . Christopher M Bishop and Nasser M Nasrabadi. 2006. Pattern recognition and machine learning. Vol. 4. Springer.

5. “An Odd Kind of Pleasure”

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