Analyzing EEG patterns in young adults exposed to different acrophobia levels: a VR study

Introduction

The primary objective of this research is to examine acrophobia, a widely prevalent and highly severe phobia characterized by an overwhelming dread of heights, which has a substantial impact on a significant proportion of individuals worldwide. The objective of our study was to develop a real-time and precise instrument for evaluating levels of acrophobia by utilizing electroencephalogram (EEG) signals.

Methods

EEG data was gathered from a sample of 18 individuals diagnosed with acrophobia. Subsequently, a range of classifiers, namely Support Vector Classifier (SVC), K-nearest Neighbors (KNN), Random Forest (RF), Decision Tree (DT), Adaboost, Linear Discriminant Analysis (LDA), Convolutional Neural Network (CNN), and Artificial Neural Network (ANN), were employed in the analysis. These methodologies encompass both machine learning (ML) and deep learning (DL) techniques.

Results

The Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) models demonstrated notable efficacy. The Convolutional Neural Network (CNN) model demonstrated a training accuracy of 96% and a testing accuracy of 99%, whereas the Artificial Neural Network (ANN) model attained a training accuracy of 96% and a testing accuracy of 97%. The findings of this study highlight the effectiveness of the proposed methodology in accurately categorizing real-time degrees of acrophobia using EEG data. Further investigation using correlation matrices for each level of acrophobia showed substantial EEG frequency band connections. Beta and Gamma mean values correlated strongly, suggesting cognitive arousal and acrophobic involvement could synchronize activity. Beta and Gamma activity correlated strongly with acrophobia, especially at higher levels.

Discussion

The results underscore the promise of this innovative approach as a dependable and sophisticated method for evaluating acrophobia. This methodology has the potential to make a substantial contribution toward the comprehension and assessment of acrophobia, hence facilitating the development of more individualized and efficacious therapeutic interventions.

Effects of virtual reality-based feedback on neurofeedback training performance—A sham-controlled study

Electroencephalography-neurofeedback (EEG-NF) has become a valuable tool in the field of psychology, e.g., to improve cognitive function. Nevertheless, a large percentage of NF users seem to be unable to control their own brain activation. Therefore, the aim of this study was to examine whether a different kind of visual feedback could positively influence NF performance after one training session. Virtual reality (VR) seems to have beneficial training effects and has already been reported to increase motivational training aspects. In the present study, we tested 61 young healthy adults (mean age: 23.48 years; 28 female) to investigate, whether 3D VR-based NF training has a more beneficial effect on the sensorimotor rhythm (SMR, 12–15 Hz) power increase than a mere 2D conventional NF paradigm. In the 3D group, participants had to roll a ball along a predefined path in an immersive virtual environment, whereas the 2D group had to increase the height of a bar. Both paradigms were presented using VR goggles. Participants completed one baseline and six feedback runs with 3 min each, in which they should try to increase SMR power over Cz. Half of the participants received real feedback whereas the other half received sham feedback. Participants receiving 3D VR-based feedback showed a linear increase in SMR power over the feedback runs within one training session. This was the case for the real as well as for the sham 3D feedback group and might be related to more general VR-related effects. The 2D group receiving the conventional bar feedback showed no changes in SMR power over the feedback runs. The present study underlines that the visual feedback modality has differential effects on the NF training performance and that 3D VR-based feedback has advantages over conventional 2D feedback.

The look at the various uses of VR

Virtual, augmented and mixed reality (VR, AR and MR) infiltrated not only gaming, industry, engineering, live events, entertainment, real estate, retail, military, etc., but as surveys indicate, also healthcare and education. In all these areas there is a lack of software development experts for VR, AR and MR to meet the needs of practice. Therefore, our intention at the Department of Computer Science, Faculty of Natural Sciences, Matej Bel University in Banská Bystrica, Slovakia, is to focus on the education and enlightenment of these areas. The aim of this article is to show the role of interactivity in different VR applications and its impact on users in three different areas: gaming, healthcare and education. In the case of one application of Arachnophobia, we also present the results of the research using a questionnaire.

The role of virtual and augmented reality in orthopedic trauma surgery: From diagnosis to rehabilitation

Virtual and augmented reality have been used to assist and improve human capabilities in many fields. Most recent advances allow the usage of these technologies for personal and professional purposes. In particular, they have been progressively introduced in many medical procedures since the last century. Thanks to immersive training systems and a better comprehension of the ongoing procedure, their main objectives are to increase patient safety and decrease recovery time. The current and future possibilities of virtual and augmented reality in the context of bone fracture reduction are the main focus of this review. This medical procedure requires meticulous planning and a complex intervention in many cases, hence becoming a promising candidate to be benefited from this kind of technology. In this paper, we exhaustively analyze the impact of virtual and augmented reality to bone fracture healing, detailing each task from diagnosis to rehabilitation. Our primary goal is to introduce novel researchers to current trends applied to orthopedic trauma surgery, proposing new lines of research. To that end, we propose and evaluate a set of qualitative metrics to highlight the most promising challenges of virtual and augmented reality technologies in this context.

Comparison between Full Body Motion Recognition Camera Interaction and Hand Controllers Interaction used in Virtual Reality Exposure Therapy for Acrophobia

Virtual Reality has already been proven as a useful supplementary treatment tool for anxiety disorders. However, no specific technological importance has been given so far on how to apply Virtual Reality with a way that properly stimulates the phobic stimulus and provide the necessary means for lifelike experience. Thanks to technological advancements, there is now a variety of hardware that can help enhance stronger emotions generated by Virtual Reality systems. This study aims to evaluate the feeling of presence during different hardware setups of Virtual Reality Exposure Therapy, and, particularly how the user's interaction with those setups can affects their sense of presence during the virtual simulation. An acrophobic virtual scenario is used as a case study by 20 phobic individuals and the Witmer-Singer presence questionnaire was used for presence evaluation by the users of the system. Statistical analysis on their answers revealed that the proposed full body Motion Recognition Cameras system generates a better feeling of presence compared to the Hand Controllers system. This is thanks to the Motion Recognition Cameras, which track and allow display of the user's entire body within the virtual environment. Thus, the users are enabled to interact and confront the anxiety-provoking stimulus as in real world. Further studies are recommended, in which the proposed system could be used in Virtual Reality Exposure Therapy trials with acrophobic patients and other anxiety disorders as well, since the proposed system can provide natural interaction in various simulated environments.