Emotion Recognition in Immersive Virtual Reality: From Statistics to Affective Computing

Javier Marín-Morales, Carmen Llinares, Jaime Guixeres, Mariano Alcañiz
<span title="2020-09-10">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Emotions play a critical role in our daily lives, so the understanding and recognition of emotional responses is crucial for human research. Affective computing research has mostly used non-immersive two-dimensional (2D) images or videos to elicit emotional states. However, immersive virtual reality, which allows researchers to simulate environments in controlled laboratory conditions with high levels of sense of presence and interactivity, is becoming more popular in emotion research.
more &raquo; ... its synergy with implicit measurements and machine-learning techniques has the potential to impact transversely in many research areas, opening new opportunities for the scientific community. This paper presents a systematic review of the emotion recognition research undertaken with physiological and behavioural measures using head-mounted displays as elicitation devices. The results highlight the evolution of the field, give a clear perspective using aggregated analysis, reveal the current open issues and provide guidelines for future research.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20185163">doi:10.3390/s20185163</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32927722">pmid:32927722</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4n6p6r3qqbf6bgjwinzdkkggje">fatcat:4n6p6r3qqbf6bgjwinzdkkggje</a> </span>
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