2021
DOI: 10.1007/s10055-021-00506-5
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Automatic detection and classification of emotional states in virtual reality and standard environments (LCD): comparing valence and arousal of induced emotions

Abstract: The following case study was carried out on a sample of one experimental and one control group. The participants of the experimental group watched the movie section from the standardized LATEMO-E database via virtual reality (VR) on Oculus Rift S and HTC Vive Pro devices. In the control group, the movie section was displayed on the LCD monitor. The movie section was categorized according to Ekman's and Russell's classification model of evoking an emotional state. The range of valence and arousal was determined… Show more

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Cited by 24 publications
(8 citation statements)
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“…When categorized by color, there were some negative words like "prison" for the black virtual environment, "horror" for the red virtual environment, and "depressed" for the green virtual environment. This kind of negative association observed with certain ambient colors may be in line with some recent studies that have explored negative emotions in VR (Lavoie et al, 2021;Magdin et al, 2021). These studies showed that virtual environments involving a higher level of absorption may increase negative emotional responses.…”
Section: Figure 10supporting
confidence: 88%
“…When categorized by color, there were some negative words like "prison" for the black virtual environment, "horror" for the red virtual environment, and "depressed" for the green virtual environment. This kind of negative association observed with certain ambient colors may be in line with some recent studies that have explored negative emotions in VR (Lavoie et al, 2021;Magdin et al, 2021). These studies showed that virtual environments involving a higher level of absorption may increase negative emotional responses.…”
Section: Figure 10supporting
confidence: 88%
“…However, the algorithms presented in the article may not necessarily be applicable only in the BCI field but may also provide models that can be adapted to other general human computer interface (HCI) implementations. Many HCIs use methods that use multiple sensors [32], the determination of certain characteristics are their processing models [33], and with regard to the methods used therein, the use of methods that have already been proven in BCI systems may also arise. The development of HCI systems can contribute to a more accurate understanding of human factors [34] and, through this, even to their development, such as the analysis and improvement of learning abilities [35].…”
Section:  Issn: 2502-4752mentioning
confidence: 99%
“…Non-invasive psychophysical tools provide an opportunity for researchers to measure a person’s emotional states [ 17 ], attention [ 18 ] or cognitive load in real time. Recently, affordable and high-resolution eye movement tracking devices have been developed to record eye movement parameters and help the eye-tracking-based research [ 19 ].…”
Section: Theoretical Backgroundmentioning
confidence: 99%