{"title":"IEEE Computational Intelligence Society Information","authors":"","doi":"10.1109/TG.2025.3603813","DOIUrl":"https://doi.org/10.1109/TG.2025.3603813","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 3","pages":"C3-C3"},"PeriodicalIF":2.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11165231","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145078566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Transactions on Games Publication Information","authors":"","doi":"10.1109/TG.2025.3603811","DOIUrl":"https://doi.org/10.1109/TG.2025.3603811","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 3","pages":"C2-C2"},"PeriodicalIF":2.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11165228","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145073214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Computational Intelligence Society Information","authors":"","doi":"10.1109/TG.2025.3575879","DOIUrl":"https://doi.org/10.1109/TG.2025.3575879","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 2","pages":"C3-C3"},"PeriodicalIF":1.7,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11038997","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Transactions on Games Publication Information","authors":"","doi":"10.1109/TG.2025.3575877","DOIUrl":"https://doi.org/10.1109/TG.2025.3575877","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 2","pages":"C2-C2"},"PeriodicalIF":1.7,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11038994","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of exergaming with or without virtual reality tools could be an alternative way of managing individuals with musculoskeletal injuries involving the upper extremities. This review aims to provide an overview on the effect of exergaming compared to other interventions such as conventional exercise therapy in treating these injuries. Randomized controlled trials related to the use of exergaming in individuals with musculoskeletal injuries involving the upper extremities that include outcome measures, such as shoulder range of motion, disability levels, pain level, and grip strength, were collected in ten different electronic databases, repository websites, and gray literature databases. Quality, risk of bias, and results of studies were systematically reviewed and meta-analyzed. A total of 12 studies fulfilling the inclusion criteria were selected. All studies indicated that exergaming, either by itself or with virtual reality tools, can help in improving all outcomes especially range of motion and disability level when compared to the control group. However, more robust randomized controlled trials are needed to further validate its effect on specific conditions, and a well-designed gaming protocol is needed to standardize treatment plans using exergaming.
{"title":"Systematic Review and Meta-Analysis: The Effect of Virtual Reality Gaming or Exergaming on Overall Recovery of Individuals With Musculoskeletal Injuries Involving the Upper Extremities","authors":"Jia Sheng Ngo;See Ziau Hoe;Maziah Mat Rosly","doi":"10.1109/TG.2025.3564874","DOIUrl":"https://doi.org/10.1109/TG.2025.3564874","url":null,"abstract":"The use of exergaming with or without virtual reality tools could be an alternative way of managing individuals with musculoskeletal injuries involving the upper extremities. This review aims to provide an overview on the effect of exergaming compared to other interventions such as conventional exercise therapy in treating these injuries. Randomized controlled trials related to the use of exergaming in individuals with musculoskeletal injuries involving the upper extremities that include outcome measures, such as shoulder range of motion, disability levels, pain level, and grip strength, were collected in ten different electronic databases, repository websites, and gray literature databases. Quality, risk of bias, and results of studies were systematically reviewed and meta-analyzed. A total of 12 studies fulfilling the inclusion criteria were selected. All studies indicated that exergaming, either by itself or with virtual reality tools, can help in improving all outcomes especially range of motion and disability level when compared to the control group. However, more robust randomized controlled trials are needed to further validate its effect on specific conditions, and a well-designed gaming protocol is needed to standardize treatment plans using exergaming.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 3","pages":"582-593"},"PeriodicalIF":2.8,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145073295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Susanna Brambilla;Giuseppe Boccignone;Nunzio Alberto Borghese;Laura A. Ripamonti
In the realm of video games, achieving a state of flow is paramount for player engagement, striking a delicate balance between boredom and anxiety. Under such circumstances, monitoring player's stress level plays a crucial role. Here, by addressing state-space dynamics, we model stress unfolding over time, allowing for both its continuous and discrete assessment. This study builds upon our previous research, advancing stress assessment techniques to enhance tailored and immersive gaming experiences through virtual reality in horror games. We provide detailed insights into our collected data, which includes physiological measurements, motion behavioral data, and participants' self-reported stress levels. In addition, we conduct an in-depth analysis on individual participants to delve deeper into the dynamics of stress experienced by each player. Results achieved give evidence that the measurement of motion behavioral data, exclusively collected from the headset, well compares to that based on electrodermal activity, more classically related to stress assessment.
{"title":"Stress Assessment in Virtual Reality Horror Games Using Players' Behavioral and Physiological Data","authors":"Susanna Brambilla;Giuseppe Boccignone;Nunzio Alberto Borghese;Laura A. Ripamonti","doi":"10.1109/TG.2025.3563258","DOIUrl":"https://doi.org/10.1109/TG.2025.3563258","url":null,"abstract":"In the realm of video games, achieving a state of flow is paramount for player engagement, striking a delicate balance between boredom and anxiety. Under such circumstances, monitoring player's stress level plays a crucial role. Here, by addressing state-space dynamics, we model stress unfolding over time, allowing for both its continuous and discrete assessment. This study builds upon our previous research, advancing stress assessment techniques to enhance tailored and immersive gaming experiences through virtual reality in horror games. We provide detailed insights into our collected data, which includes physiological measurements, motion behavioral data, and participants' self-reported stress levels. In addition, we conduct an in-depth analysis on individual participants to delve deeper into the dynamics of stress experienced by each player. Results achieved give evidence that the measurement of motion behavioral data, exclusively collected from the headset, well compares to that based on electrodermal activity, more classically related to stress assessment.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 3","pages":"827-838"},"PeriodicalIF":2.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145078686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Computational Intelligence Society Information","authors":"","doi":"10.1109/TG.2025.3546830","DOIUrl":"https://doi.org/10.1109/TG.2025.3546830","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 1","pages":"C3-C3"},"PeriodicalIF":1.7,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10931174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Transactions on Games Publication Information","authors":"","doi":"10.1109/TG.2025.3546832","DOIUrl":"https://doi.org/10.1109/TG.2025.3546832","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 1","pages":"C2-C2"},"PeriodicalIF":1.7,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10931175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, we tackle the problem of designing an efficient bidding strategy for simultaneous ascending auctions (SAA). SAA is a well-known mechanism for allocating spectrum to mobile networks operators and has been used for example to allocate 5G licenses in many countries. Although the rules are relatively simple, there is no known optimal bidding strategy for SAA. In a previous work, we proposed a Simultaneous move Monte Carlo Tree Search-based algorithm named $SMS^{alpha }$ that we extend here to an incomplete information framework. We consider and compare three determinization approaches of $SMS^{alpha }$, and show how they are able to tackle four key strategic issues of SAA, namely, the exposure problem, the own price effect, the budget constraints and the eligibility management. Extensive numerical experiments on instances of realistic size and including an uncertain framework show that our extensions of $SMS^{alpha }$ outperform state-of-the-art algorithms by achieving higher expected utility while taking less risks.
{"title":"Bidding Efficiently in Simultaneous Ascending Auctions With Incomplete Information Using Monte Carlo Tree Search and Determinization","authors":"Alexandre Pacaud;Aurelien Bechler;Marceau Coupechoux","doi":"10.1109/TG.2025.3552025","DOIUrl":"https://doi.org/10.1109/TG.2025.3552025","url":null,"abstract":"In this article, we tackle the problem of designing an efficient bidding strategy for simultaneous ascending auctions (SAA). SAA is a well-known mechanism for allocating spectrum to mobile networks operators and has been used for example to allocate 5G licenses in many countries. Although the rules are relatively simple, there is no known optimal bidding strategy for SAA. In a previous work, we proposed a Simultaneous move Monte Carlo Tree Search-based algorithm named <inline-formula><tex-math>$SMS^{alpha }$</tex-math></inline-formula> that we extend here to an incomplete information framework. We consider and compare three determinization approaches of <inline-formula><tex-math>$SMS^{alpha }$</tex-math></inline-formula>, and show how they are able to tackle four key strategic issues of SAA, namely, the exposure problem, the own price effect, the budget constraints and the eligibility management. Extensive numerical experiments on instances of realistic size and including an uncertain framework show that our extensions of <inline-formula><tex-math>$SMS^{alpha }$</tex-math></inline-formula> outperform state-of-the-art algorithms by achieving higher expected utility while taking less risks.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 3","pages":"813-826"},"PeriodicalIF":2.8,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145078663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rongyang Li;Jianguo Ding;Huansheng Ning;Lingfeng Mao
Biosignal sequence real-time prediction (BSRP) is essential for predicting the future emotional experience of game users. However, BSRP for game users faces challenges, including poor real-time performance and limited feature fusion dimensions. To address these issues, we proposed a method for BSRP based on the features fusion of local–global and time–frequency domain (LGTF) for game users, which integrates real-time capabilities with multidimensional features fusion. Specifically, LGTF meets real-time requirements and achieves the features fusion of local–global (LG) through multichannel synchronized adaptive convolution. In addition, LGTF implements the features fusion of interband and intraband in the frequency domain and the features fusion of time–frequency (TF) domain by incorporating the self-attention mechanism and Fourier Transform. Furthermore, we conducted comprehensive validation experiments on LGTF using the public dataset. The results indicate that: first, in the comparison study, LGTF outperformed other methods, achieving the lowest average mean squared error (MSE) and mean absolute error values across different prediction lengths of 0.61 and 0.47, respectively. Second, ablation studies revealed that the addition of TF domain feature fusion and LG feature fusion both have the positive effect on the prediction performance, reducing the average MSE by 0.11 and 0.09, respectively. Third, generalization study shows that LGTF exhibits stable performance and generalization across different subjects and shows performance advantages in specific game scenarios. Fourth, time performance analysis suggests LGTF has the real-time performance. Finally, case study demonstrates that LGTF is practical for predicting game users' future emotions and enhancing their emotional experiences.
{"title":"Biosignal Sequence Real-Time Prediction for Game Users Based on Features Fusion of Local–Global and Time–Frequency Domain","authors":"Rongyang Li;Jianguo Ding;Huansheng Ning;Lingfeng Mao","doi":"10.1109/TG.2025.3550779","DOIUrl":"https://doi.org/10.1109/TG.2025.3550779","url":null,"abstract":"Biosignal sequence real-time prediction (BSRP) is essential for predicting the future emotional experience of game users. However, BSRP for game users faces challenges, including poor real-time performance and limited feature fusion dimensions. To address these issues, we proposed a method for BSRP based on the features fusion of local–global and time–frequency domain (LGTF) for game users, which integrates real-time capabilities with multidimensional features fusion. Specifically, LGTF meets real-time requirements and achieves the features fusion of local–global (LG) through multichannel synchronized adaptive convolution. In addition, LGTF implements the features fusion of interband and intraband in the frequency domain and the features fusion of time–frequency (TF) domain by incorporating the self-attention mechanism and Fourier Transform. Furthermore, we conducted comprehensive validation experiments on LGTF using the public dataset. The results indicate that: first, in the comparison study, LGTF outperformed other methods, achieving the lowest average mean squared error (MSE) and mean absolute error values across different prediction lengths of 0.61 and 0.47, respectively. Second, ablation studies revealed that the addition of TF domain feature fusion and LG feature fusion both have the positive effect on the prediction performance, reducing the average MSE by 0.11 and 0.09, respectively. Third, generalization study shows that LGTF exhibits stable performance and generalization across different subjects and shows performance advantages in specific game scenarios. Fourth, time performance analysis suggests LGTF has the real-time performance. Finally, case study demonstrates that LGTF is practical for predicting game users' future emotions and enhancing their emotional experiences.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 3","pages":"797-812"},"PeriodicalIF":2.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145073273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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