Pressure at play:measuring player approach and avoidance behaviour through the keyboard

With the increased adoption of real-time objective measurements of player experience, advances have been made in characterising the dynamically changing aspects of the player experience during gameplay itself. A direct coupling to player action, however, is not without challenges. Many physiological responses, for instance, have an inherent delay, and often take some time to return to a baseline, providing challenges of interpretation when analysing rapidly changing gameplay on a micro level of interaction. The development of event-related, or phasic, measurements directly coupled to player actions provides additional insights, for instance through player modelling, but also through the use of behavioural characteristics of the human computer interaction itself. In this study, we focused on the latter, and measured keyboard pressure in a number of different, fast-paced action games. In this particular case, we related specific functional game actions (keyboard presses) to experiential player behaviour. We found keyboard pressure to be higher for avoidance as compared to approach-oriented actions. Additionally, the difference between avoidance and approach keyboard pressure related to levels of arousal. The findings illustrate the application potential of qualifying players’ functional actions at play (navigating in a game) and interpret player experience related to these actions through players’ real world behavioural characteristics like interface pressure

Affective Game Computing: A Survey

This paper surveys the current state of the art in affective computing principles, methods and tools as applied to games. We review this emerging field, namely affective game computing, through the lens of the four core phases of the affective loop: game affect elicitation, game affect sensing, game affect detection and game affect adaptation. In addition, we provide a taxonomy of terms, methods and approaches used across the four phases of the affective game loop and situate the field within this taxonomy. We continue with a comprehensive review of available affect data collection methods with regards to gaming interfaces, sensors, annotation protocols, and available corpora. The paper concludes with a discussion on the current limitations of affective game computing and our vision for the most promising future research directions in the field

User modelling for adaptive training in high performance driving

User model creation is a fundamental component for the development of intelligent personalised systems. This thesis proposes an adaptive user modelling framework that uses a combination of unobtrusive task-related and physiological data with the aim of identifying strengths and weaknesses in user performance in the defined task. The research is focused on utilising the framework to provide personalised content adaptation in car racing games. Our system adopts concepts from the Trace Theory (TT) framework, and uses machine learning techniques to extract specific features from the user and the game. These metrics are then transformed and evaluated into higher level abstractions such as experience, exploration and physiological attention by utilising the educational theoretical frameworks of Flow and Zone Theory. The end result is to provide new game paths utilising the user’s model. We demonstrate that this procedural generation of user-tailored content drives the self-motivating behaviour of players to immerse and engage themselves in the game’s virtual world. Collection of data and feedback from multiple users (52) allowed us to associate the model’s outcomes to the user responses, as well as device multiple trial scenarios to verify their training and engagement. We have also evaluated the algorithms for the generation of new tracks for their suitability on the skill’s profile of 41 of our subjects and race track diversity among the evolved paths. We have also designed a method for predicting the states of the user-controlled system by combining information from both sources – vehicle and user – via Gaussian Processes (GPs). In the context of high speed car racing we showed that the forthcoming position and speed of the car can be predicted with high accuracy by our trained user models. This opens up future possibilities of generating better personalised tracks for individuals or even real-time share-control of the car to optimally assist the users in dangerous situations.Open Acces

A taxonomy and state of the art revision on affective games

Affective Games are a sub-field of Affective Computing that tries to study how to design videogames that are able to react to the emotions expressed by the player, as well as provoking desired emotions to them. To achieve those goals it is necessary to research on how to measure and detect human emotions using a computer, and how to adapt videogames to the perceived emotions to finally provoke them to the players. This work presents a taxonomy for research on affective games centring on the aforementioned issues. Here we devise as well a revision of the most relevant published works known to the authors on this area. Finally, we analyse and discuss which important research problem are yet open and might be tackled by future investigations in the area of Affective GamesThis work has been co-funded by the following research projects: EphemeCH (TIN2014-56494-C4-{1,4}-P) and DeepBio (TIN2017-85727-C4-3-P) by Spanish Ministry of Economy and Competitivity, under the European Regional Development Fund FEDER, and Justice Programme of the European Union (2014–2020) 723180 – RiskTrack – JUST-2015-JCOO-AG/JUST-2015-JCOO-AG-

Enhancing health care via affective computing

Affective computing is a multidisciplinary field that studies the various ways by which computational processes are able to elicit, sense, and detect manifestations of human emotion. While the methods and technology delivered by affective computing have demonstrated very promising results across several domains, their adoption by healthcare is still at its initial stages. With that aim in mind, this commentary paper introduces affective computing to the readership of the journal and praises for the benefits of affect-enabled systems for prognostic, diagnostic and therapeutic purposes.peer-reviewe

Modelling Aggressive or Risky Driving: The Effect of Cinematic Portrayals of Risky Driving

The purpose of the current research was to investigate the influence of motion pictures, depicting aggressive or risky driving, on subsequent driving behaviour. Both experimental and descriptive research approaches were used in an attempt to demonstrate the robustness of this relationship. Study 1 employed an experimental design, in which participants drove through a test course on a driving simulator following exposure to either neutral, arousing, or aggressive and risky driving movie content. Various person, situation, and internal factors were assessed, along with various measures of aggressive or risky driving (e.g., speed, acceleration, passing frequency). Study 2 was an event study, which linked automated enforcement speeding data, from the City of Edmonton, to the release of two aggressive or risky driving movies (i.e., Fast and Furious 6 and Furious 7) to investigate changes in the number of speeding infractions and speed differential (i.e., amount the driver exceeded the posted speed limit). Multiple years of speeding infraction data provided a built in replication, allowing for comparisons across different years. The results from Study 1 provided evidence for the contribution of trait aggression, sensation seeking, driving vengeance, a history of violation (i.e., particularly speeding), and a provoking racing scenario to the modelling of aggressive or risky driving. Study 2 revealed an increase in the number of speeding infractions and mean speed differential for the opening weekend and first week post-movie release for Furious 7. The findings from these studies demonstrate the interactivity of person, internal, and situation factors in the modelling of aggressive or risky driving and suggest that movies, which depict this content, can influence real-world speeding behaviour. Public policy implications are addressed, with a strong suggestion for increased enforcement following the release of such movies, particularly during the first week. An emphasis is placed on production companies to provide warnings and address unsafe driving as a public health and safety concern. Also, viewers of such material are reminded of their responsibility, as drivers, to engage in thoughtful, non-risky action when presented with an aggressive driving opportunity