The area of biofeedback interaction has grown over recent years, thanks to the release of more affordable and reliable sensor technology, and the accessibility offered by modern game development tools. This article presents a systematic literature review focusing on how different biofeedback interaction methods have been used for entertainment purposes in video games, between 2008 and 2020. It divides previous contributions in terms of a proposed interaction classification criteria and five different biofeedback methods (with a sixth category combining them): electroencephalography, electrocardiography, eye tracking, electrodermal activity, electromyography, and multi-modal interaction. The review describes the properties, sensor technologies, and the type of data gathered for every included biofeedback method, and presents their respective interaction techniques. It summarizes a set of opportunities and challenges for each included method, based on the results from previous work, and discusses these findings. It also analyzes how these interaction techniques are distributed between different common game genres. The review is beneficial for people interested in biofeedback methods and their potential use for novel interaction techniques in future video games. © 2021 ACM.

Due to an increase in affordable, reliable and non-intrusive eye trackers the technology has recently been used by the video game industry. This course offers participants the opportunity to get an update on research and developments in gaze-based interaction techniques in combination with other sensors. The course consists of three parts: (1) a review of eye tracking analysis and interaction in video games and virtual reality applications, (2) possibilities and challenges with gaze-based interaction, and (3) lessons learned from developing a commercial video game application using eye tracking along with alternative virtual reality technologies. This course is relevant for everyone who is interested in developing games that use eye tracking as an interaction device. The content is suitable for beginners or experienced delegates who want to learn more about the state of the art and future possibilities in eye tracking combined with other sensors as interaction devices. We believe that games and virtual reality applications have just started to incorporate these new techniques and further research and developments are needed in order to evaluate novel ways to enhance gameplay.

The following article offers a set of recommendations that are considered relevant for designing and executing experiences with Virtual Reality (VR) technology. It presents a brief review of the history and evolution of VR, along with the physiological issues related to its use. Additionally, typical practices in VR, used by both academia and industry are discussed and contrasted. These were further analysed from an ethical perspective, guided by legal and Corporate Social Responsibility (CSR) frameworks, to understand their motivation and goals, and the rights and responsibilities related to the exposure of research participants and final consumers to VR. Our results showed that there is a significant disparity between practices in academia and industry, and for industry specifically, there can be breaches of user protection regulations and poor ethical practices. The differences found are mainly in regards to the type of content presented, the overall setup of VR experiences, and the amount of information provided to participants or consumers respectively. To contribute to this issue, this study highlights some ethical aspects and also offers practical considerations that aim, not only to have more appropriate practices with VR in public spaces but also to motivate a discussion and reflection to ease the adoption of this technology in the consumer market.

An important aspect of virtual reality (VR) interfaces are novel natural user interactions (NUIs). The increased use of VR games requires the evaluation of novel interaction techniques that allow efficient manipulations of 3D elements using the hands of the player. Examples of VR devices that support these interactions include the HTC Vive controller and the Leap Motion sensor. This paper presents a quantitative and qualitative evaluation of player performance and experience in a controlled experiment with 20 volunteering participants. The experiment evaluated the HTC Vive controller and the Leap Motion sensor when manipulating 3D objects in two VR games. The first game was a Pentomino puzzle and the second game consisted of a ball-throwing task. Four interaction techniques (picking up, dropping, rotating, and throwing objects) were evaluated as part of the experiment. The number of user interactions with the Pentomino pieces, the number of ball throws, and game completion time were metrics used to analyze the player performance. A questionnaire was also used to evaluate the player experience regarding enjoyment, ease of use, sense of control and user preference. The overall results show that there was a significant decrease in player performance when using the Leap Motion sensor for the VR game tasks. Participants also reported that hand gestures with the Leap Motion sensor were not as reliable as the HTC Vive controller. However, the survey showed positive responses when using both technologies. The paper also offers ideas to keep exploring the capabilities of NUI techniques in the future. Copyright © 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

Thanks to its effectiveness, electrodermal activity (EDA) has been previously included as an evaluation metric, within analyses of user experience. In this study, the phasic component of participants’ EDA data is examined in relation to their reported experiences when playing a set of virtual reality games, that featured the HTC Vive and Leap Motion controllers for input. Two models are used in the analysis of the phasic component: a deconvolution model and a convex optimization model. Despite having significant differences in their player experiences, results indicate that there are not many significant differences in the phasic component data. Even if some weak correlations were found, the majority of results show no linear correlations between the phasic component data and the reported experience variables. This shows that the phasic component of EDA data should be further investigated in conjunction with other psychophysiological signals because it has only recently demonstrated a weak link with player experience. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Electrodermal activity is considered one of the more reliable methodologies to assess emotional arousal, and it has been adopted as an alternative method for the analysis of player experience in video game research. In this study, we present a quantitative evaluation of self-contained electrodermal measurements, focusing on the analysis of the tonic component and its potential relationship with player experience. The analysis presents a frequency-domain feature quantification of the tonic component, named gradual changes. With it, we evaluate how the variation of the tonic component correlates with the player experience valence, in a set virtual reality games. The analysis also offers an evaluation of the prediction capabilities of the gradual changes, to classify player experience, using a supervised learning approach. Our results support the idea that the tonic component correlates with player experience, statistically demonstrating that a higher number of gradual changes feature a directly proportional relationship with a negative valence in player experience. Despite this, the gradual changes featured a rather limited prediction capability upon player experience, motivating future work in this area.