2,964 research outputs found

    An Analysis of Physiological and Psychological Responses in Virtual Reality and Flat Screen Gaming

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    Recent research has focused on the effectiveness of Virtual Reality (VR) in games as a more immersive method of interaction. However, there is a lack of robust analysis of the physiological effects between VR and flatscreen (FS) gaming. This paper introduces the first systematic comparison and analysis of emotional and physiological responses to commercially available games in VR and FS environments. To elicit these responses, we first selected four games through a pilot study of 6 participants to cover all four quadrants of the valence-arousal space. Using these games, we recorded the physiological activity, including Blood Volume Pulse and Electrodermal Activity, and self-reported emotions of 33 participants in a user study. Our data analysis revealed that VR gaming elicited more pronounced emotions, higher arousal, increased cognitive load and stress, and lower dominance than FS gaming. The Virtual Reality and Flat Screen (VRFS) dataset, containing over 15 hours of multimodal data comparing FS and VR gaming across different games, is also made publicly available for research purposes. Our analysis provides valuable insights for further investigations into the physiological and emotional effects of VR and FS gaming.Comment: This work has been submitted to the IEEE Transactions on Affective Computing for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

    Comparison of engagement and emotional responses of older and younger adults interacting with 3D cultural heritage artefacts on personal devices

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    The availability of advanced software and less expensive hardware allows museums to preserve and share artefacts digitally. As a result, museums are frequently making their collections accessible online as interactive, 3D models. This could lead to the unique situation of viewing the digital artefact before the physical artefact. Experiencing artefacts digitally outside of the museum on personal devices may affect the user's ability to emotionally connect to the artefacts. This study examines how two target populations of young adults (18–21 years) and the elderly (65 years and older) responded to seeing cultural heritage artefacts in three different modalities: augmented reality on a tablet, 3D models on a laptop, and then physical artefacts. Specifically, the time spent, enjoyment, and emotional responses were analysed. Results revealed that regardless of age, the digital modalities were enjoyable and encouraged emotional responses. Seeing the physical artefacts after the digital ones did not lessen their enjoyment or emotions felt. These findings aim to provide an insight into the effectiveness of 3D artefacts viewed on personal devices and artefacts shown outside of the museum for encouraging emotional responses from older and younger people

    Virtual reality and stimulation of touch and smell for inducing relaxation: A randomized controlled trial

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    The aim of this study was to test the efficacy of a mood-induction procedure in a Virtual Reality (VR-MIP) environment for inducing relaxation and generating sense of presence, and to test whether the stimulation of the senses of touch and smell improves the efficacy of this VR-MIP. A controlled study was carried out with four experimental conditions. All of them included the VR-MIP to induce relaxation, but varying the senses stimulated. The sample consisted of 136 participants randomly assigned to one of the four experimental conditions. Emotions and sense of presence were evaluated. The results showed statistical differences before and after mood-induction and a high sense of presence in all groups. However, no statistical differences were found among the four groups on emotions and sense of presence. The results showed that the VR-MIP was effective; however, the stimulation of the senses of touch and smell did not show significate improve of the mood-induction or the sense of presence. It was identified a trend in favor of the groups where the sense of touch was stimulated, they seemed more relaxed and the sense of presence was higher. We hypothesized that the stimulation of sense of touch, could improve the efficacy when using VR-MIP because it provides more sensory information.This work was funded by the 4Senses project (PSE-020400-2007-1) and the Consolider project (SEJ2006-14301/PSIC) of the Ministry of Science and Innovation in Spain (Ministerio de Ciencia e Innovación de España)

    Autonomous Assessment of Videogame Difficulty Using Physiological Signals

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    Given the well-explored relation between challenge and involvement in a task, (e.g., as described in Csikszentmihalyi’s theory of flow), it could be argued that the presence of challenge in videogames is a core element that shapes player experiences and should, therefore, be matched to the player’s skills and attitude towards the game. However, handling videogame difficulty, is a challenging problem in game design, as too easy a task can lead to boredom and too hard can lead to frustration. Thus, by exploring the relationship between difficulty and emotion, the current work intends to propose an artificial intelligence model that autonomously predicts difficulty according to the set of emotions elicited in the player. To test the validity of this approach, we developed a simple puzzle-based Virtual Reality (VR) videogame, based on the Trail Making Test (TMT), and whose objective was to elicit different emotions according to three levels of difficulty. A study was carried out in which physiological responses as well as player self- reports were collected during gameplay. Statistical analysis of the self-reports showed that different levels of experience with either VR or videogames didn’t have a measurable impact on how players performed during the three levels. Additionally, the self-assessed emotional ratings indicated that playing the game at different difficulty levels gave rise to different emotional states. Next, classification using a Support Vector Machine (SVM) was performed to verify if it was possible to detect difficulty considering the physiological responses associated with the elicited emotions. Results report an overall F1-score of 68% in detecting the three levels of difficulty, which verifies the effectiveness of the adopted methodology and encourages further research with a larger dataset.Dada a relação bem explorada entre desafio e envolvimento numa tarefa (p. ex., con- forme descrito na teoria do fluxo de Csikszentmihalyi), pode-se argumentar que a pre- sença de desafio em videojogos é um elemento central que molda a experiência do jogador e deve, portanto, ser compatível com as habilidades e a atitude que jogador exibe perante o jogo. No entanto, saber como lidar com a dificuldade de um videojogo é um problema desafiante no design de jogos, pois uma tarefa muito fácil pode gerar tédio e muito di- fícil pode levar à frustração. Assim, ao explorar a relação entre dificuldade e emoção, o presente trabalho pretende propor um modelo de inteligência artificial que preveja de forma autônoma a dificuldade de acordo com o conjunto de emoções elicitadas no jogador. Para testar a validade desta abordagem, desenvolveu-se um jogo de puzzle em Realidade Virtual (RV), baseado no Trail Making Test (TMT), e cujo objetivo era elicitar diferentes emoções tendo em conta três níveis de dificuldade. Foi realizado um estudo no qual se recolheram as respostas fisiológicas, juntamente com os autorrelatos dos jogado- res, durante o jogo. A análise estatística dos autorelatos mostrou que diferentes níveis de experiência com RV ou videojogos não tiveram um impacto mensurável no desempenho dos jogadores durante os três níveis. Além disso, as respostas emocionais auto-avaliadas indicaram que jogar o jogo em diferentes níveis de dificuldade deu origem a diferentes estados emocionais. Em seguida, foi realizada a classificação por intermédio de uma Má- quina de Vetores de Suporte (SVM) para verificar se era possível detectar dificuldade, considerando as respostas fisiológicas associadas às emoções elicitadas. Os resultados re- latam um F1-score geral de 68% na detecção dos três níveis de dificuldade, o que verifica a eficácia da metodologia adotada e incentiva novas pesquisas com um conjunto de dados maior

    Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training

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    Cognitive training has shown promising results for delivering improvements in human cognition related to attention, problem solving, reading comprehension and information retrieval. However, two frequently cited problems in cognitive training literature are a lack of user engagement with the training programme, and a failure of developed skills to generalise to daily life. This paper introduces a new cognitive training (CT) paradigm designed to address these two limitations by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task. Additionally, it incorporates facial electromyography (EMG) as a means of determining user affect while engaged in the CT task. This information is then utilised to dynamically adjust the game's difficulty in real-time as users play, with the aim of leading them into a state of flow. Affect recognition rates of 64.1% and 76.2%, for valence and arousal respectively, were achieved by classifying a DWT-Haar approximation of the input signal using kNN. The affect-aware VR cognitive training intervention was then evaluated with a control group of older adults. The results obtained substantiate the notion that adaptation techniques can lead to greater feelings of competence and a more appropriate challenge of the user's skills

    Co-Design with Myself: A Brain-Computer Interface Design Tool that Predicts Live Emotion to Enhance Metacognitive Monitoring of Designers

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    Intuition, metacognition, and subjective uncertainty interact in complex ways to shape the creative design process. Design intuition, a designer's innate ability to generate creative ideas and solutions based on implicit knowledge and experience, is often evaluated and refined through metacognitive monitoring. This self-awareness and management of cognitive processes can be triggered by subjective uncertainty, reflecting the designer's self-assessed confidence in their decisions. Despite their significance, few creativity support tools have targeted the enhancement of these intertwined components using biofeedback, particularly the affect associated with these processes. In this study, we introduce "Multi-Self," a BCI-VR design tool designed to amplify metacognitive monitoring in architectural design. Multi-Self evaluates designers' affect (valence and arousal) to their work, providing real-time, visual biofeedback. A proof-of-concept pilot study with 24 participants assessed its feasibility. While feedback accuracy responses were mixed, most participants found the tool useful, reporting that it sparked metacognitive monitoring, encouraged exploration of the design space, and helped modulate subjective uncertainty
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