The Influence of Brain Activity on the Interactive Process through Biofeedback Mechanisms in Virtual Reality Environments

Costa, Rita; Gomes, Paulo Veloso; Correia, António; Marques, António; Pereira, Javier

doi:10.3390/engproc2021007015

Cited by 2 publications

(3 citation statements)

References 4 publications

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“…, 2020). The device collects delta (1–3 Hz), theta (3–8 Hz), alpha (8–12 Hz), beta (12–38 Hz) and gamma (38–45 Hz) brainwaves from the brain's prefrontal area through the AF3, AF4, AF7, AF8, Fp1 and Fp2 channels with a sampling rate of 500 Hz (Costa et al. , 2021).…”

Section: Methodsmentioning

confidence: 99%

“…Additionally, it offers several advantages throughout the experiment, such as using a unified device that removes mobility and artifact problems (S a et al, 2020). The device collects delta (1-3 Hz), theta (3-8 Hz), alpha (8-12 Hz), beta (12-38 Hz) and gamma (38-45 Hz) brainwaves from the brain's prefrontal area through the AF3, AF4, AF7, AF8, Fp1 and Fp2 channels with a sampling rate of 500 Hz (Costa et al, 2021). Additionally, the device tracks EEG signals with yielding attributes like attention, relaxation and brain balance.…”

Section: Human Experiences In Vrmentioning

confidence: 99%

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The impact of urban graffiti with facial expressions on human behavioral and emotional experiences in a VR environment

Karakas,

Dumlu,

Sarıkaya

et al. 2023

ARCH

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PurposeThe present study investigates human behavioral and emotional experiences based on human-built environment interaction with a specific interest in urban graffiti displaying fear and pleasure-inducing facial expressions. Regarding human behavioral and emotional experience, two questions are asked for the outcome of human responses and two hypotheses are formulated. H1 is based on the behavioral experience and posits that the urban graffiti displaying fear and pleasure-inducing facial expressions elicit specified behavioral fear and pleasure responses. H2 is based on emotional experience and states that the urban graffiti displaying fear and pleasure-inducing facial expressions elicit specified emotional fear and pleasure responses.Design/methodology/approachThe research design is developed as a multi-method approach, applying a lab-based experimental strategy (N:39). The research equipment includes a mobile electroencephalogram (EEG) and a Virtual Reality (VR) headset. The behavioral and emotional human responses concerning the representational features of urban graffiti are assessed objectively by measuring physiological variables, EEG signals and subjectively by behavioral variables, systematic behavioral observation and self-report variables, Self-assessment Manikin (SAM) questionnaire. Additionally, correlational analyses between behavioral and emotional results are performed.FindingsThe findings of behavioral and emotional evaluations and correlational results show that specialized fear and pleasure response patterns occur due to the affective characteristics of the urban graffiti's representational features, supporting our hypotheses. As a result, the characteristics of behavioral fear and pleasure response and emotional fear and pleasure response are identified.Originality/valueThe present paper contributes to the literature on human-built environment interactions by using physiological, behavioral and self-report measurements as indicators of human behavioral and emotional experiences. Additionally, the literature on urban graffiti is expanded by studying the representational features of urban graffiti as a parameter of investigating human experience in the built environment.

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Section: Methodsmentioning

confidence: 99%

Section: Human Experiences In Vrmentioning

confidence: 99%

The impact of urban graffiti with facial expressions on human behavioral and emotional experiences in a VR environment

Karakas,

Dumlu,

Sarıkaya

et al. 2023

ARCH

View full text Add to dashboard Cite

show abstract

“…Looxid Link is a VR headset-compatible hardware configuration that includes a frontal six-channel EEG system (F3, F4, F7, F8, Fp1, and Fp2) conforming to International System 10-10 [20] (see Figure 4). Unlike conventional wet-EEG with wires and voluminous amplifiers, wireless dry-electrode mobile EEG allows for effortless attachment to the VR headset and it is virtually unnoticeable by the user [21]. Table 2 shows the data generated at the output of the device.…”

Section: Eegmentioning

confidence: 99%

Recognition of Human Mental Stress Using Machine Learning: A Case Study on Refugees

Kamińska

2023

Electronics

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This paper introduces a study on stress recognition utilizing mobile EEG and GSR sensors. The research involved collecting samples from a group of 55 refugees who participated in Virtual Reality stress-reduction sessions. The timing of the study coincided with an influx of refugees, prompting the development of software specifically designed to alleviate acute stress among them. The paper focuses on presenting an EEG/GSR signals pipeline for classifying stress levels, emphasizing selecting the most informative features. The classification process employed popular machine learning methods, yielding results of 86.7% for two-stress-level classification and 82.3% and 67.7% for the three- and five-level classifications, respectively. Most importantly, the positive impact of the system has been proven by subjective assessment in alignment with objective features analysis. Such a system has not yet reached the level of autonomy, but it can be a valuable support tool for mental health professionals.

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The Influence of Brain Activity on the Interactive Process through Biofeedback Mechanisms in Virtual Reality Environments

Cited by 2 publications

References 4 publications

The impact of urban graffiti with facial expressions on human behavioral and emotional experiences in a VR environment

The impact of urban graffiti with facial expressions on human behavioral and emotional experiences in a VR environment

Recognition of Human Mental Stress Using Machine Learning: A Case Study on Refugees

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