Being present in a real or virtual world: A EEG study
Introduction
The virtual reality (VR) is a synthetic spatial (usually 3D) world which is perceived from the first person point of view in real time [1]. The VR is typical hardware-software with input/output devices for tasks of human interaction At the same time, VR applications may influence emotions [2] and psychophysiological features of humans [3] deeply in the form of immersion or presence [4]. The presence is key feature of VR because it may increase efficiency of man-machine interaction (MMI) [5] based on enlarged sensory or other ways of information perception [6].
The nature of the presence is discussed at different angles. On the one side, there is an empirical correlation of immersion with hardware and software parameters of the VR such as a frame rate, tracking a head rotation, audio, and interaction methods applied in the VR [7]. On the other side, a deep level of presence can be explained by activation of similar structures in the brain and sensory stimuli as in the real world [8].
In this context, the objective evaluation of presence in VR is rather challenging. There are subjective methods for measuring of presence based on standard software methods as heuristic methods, usability testing and questionnaires. [9]. Regardless, virtual environment (VE) makes a strong psychophysiological impact on an individual, so monitoring stress or psychophysiological features are more actual [10].
In recent times psychophysiological data recorders have become widespread. Such systems assess and measure the parameters like stress level [2], an emotional [11] and affected state and eye tracking [12]. For example, it was shown that attentional processes seem to crucially shape the interplay between presence and affective responses [13] and emotional reaction in subjects with experiments using virtual food, when real and virtual exposures elicit a comparable emotional reaction in subjects [14].
These systems take into account some psychophysiological parameters that describe the internal state of an individual. However, it does not allow for a comprehensive examination of VR perception that may include several levels of information perception and processing at once. Therefore, we believe that the monitoring of brain cortex electrical activity may be the most appropriate method for measuring presence in VR. For these purposes we apply electroencephalography that gives us an opportunity to monitor an internal state of an individual by means of visualization of bioelectrical potential level distribution (a toposcope). This method in combination with electrocardiography (ECG), electrooculography (EOG) and electromyography (EMG) forms a comprehensive picture of purposeful actions related to bioenergy expenditure, the activity of neurosynaptic connections, blood pressure, etc. In addition, the present-day computing facilities and software packages ensure visualization of anatomic structures over time [45].
By now EEG devices have successfully been applied with VR; these hybrid systems give a grounding for a brain-computer interface (BCI). Such system has been applied to rehabilitation of motor functions [15], development of motor skills [16], an authentication process [17], etc. The electroencephalography may be a tool for measuring of presence in regard to verisimilitude and accuracy of action purposefulness – this may become a promising research trend. At least, this issue has already arisen in a number of practical problem solutions.
Section snippets
Theoretical overview
One of the most common applications of VR is simulation training in the different spheres such as medicine [18], astronautic science [19], education [20], industry [21], sports [22], military training [23], games [24], building architecture [25], etc. Therefore, VR should reproduce a user's practical activity in the context of any task. This causes a need to evaluate and measure VR verisimilitude. A wide array of professional activities is related with different kinds of risks: hazards to life,
Subjects and equipment
Five normal males (50 ± 5 years old), instructors of the Russian Mountain School, became subjects of the experiment voluntarily and free of charge. All the subjects were right-handers, had no health concerns in relation of sight, the vestibular system or neural disorders. They have never used a HTCVive headset before (1080 × 1200px, 90 Hz, 512 g).
The study was based on the EEG-signals recorded by an ENCEPHALAN-EEGR-19/26 electroencephalograph-recorder, a product of the Medikom MTD company. The
Results and discussion
The data obtained from the toposcope within two seconds when performing one cycle of a turn (entering into a turn – an active phase of a turn – exiting from a turn) on the sloping surface allow comparing frequency parameters in the different brain regions as shown in Fig. 5, Fig. 6, Fig. 7. The differences are shown in the symmetrical brain lobes (power and frequency asymmetry), in the frontal and occipital lobes of the brain, these are differences in dominant and weighted average frequencies
Conclusion
The current study revealed relatively stable neuropatterns mostly in the virtual and physical environment and to a lesser degree in the desktop application. We successfully revealed relatively stable activation areas in the brain within the relative frequency spectra even without full suppression of artifacts. We can suppose that there is a connection between brain activity and purposeful activity of an individual in the virtual and physical environments, and consequently, there is no such
Author agreement
We confirm that all authors have seen and approved the final version of the manuscript being submitted.
Authors warrant that the article is the original work, hasn't received prior publication and isn't under consideration for publication elsewhere.
Declaration of Competing Interest
The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Acknowledgement
The research outcomes are obtained with the support of the Ministry of Education and Science of the Russian Federation, grant No. 25.1095.2017/4.6.
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