2,964 research outputs found
An Analysis of Physiological and Psychological Responses in Virtual Reality and Flat Screen Gaming
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
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
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
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 compatĂvel com as habilidades e a atitude que jogador exibe perante
o jogo. No entanto, saber como lidar com a dificuldade de um videojogo Ă© um problema
desafiante no design de jogos, pois uma tarefa muito fácil pode gerar tédio e muito di-
fĂcil pode levar Ă frustração. Assim, ao explorar a relação entre dificuldade e emoção,
o presente trabalho pretende propor um modelo de inteligĂŞncia 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 trĂŞs nĂveis de dificuldade. Foi realizado um estudo no
qual se recolheram as respostas fisiolĂłgicas, juntamente com os autorrelatos dos jogado-
res, durante o jogo. A análise estatĂstica dos autorelatos mostrou que diferentes nĂveis de
experiência com RV ou videojogos não tiveram um impacto mensurável no desempenho
dos jogadores durante os trĂŞs nĂveis. AlĂ©m disso, as respostas emocionais auto-avaliadas
indicaram que jogar o jogo em diferentes nĂveis 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 possĂvel detectar dificuldade,
considerando as respostas fisiológicas associadas às emoções elicitadas. Os resultados re-
latam um F1-score geral de 68% na detecção dos trĂŞs nĂveis 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
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
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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