Search Results (7)

Background: Specific phobias impact over 400 million people worldwide. Digitalizing mental health could alleviate the burden. Still, although the corporate-driven Metaverse is expanding rapidly, there needs to be more momentum in harnessing virtual reality exposure therapy uptake. Objective: This study aims to conceptualize, develop, and deploy a free Virtual Reality Exposure Therapy (VRET) application specifically designed for treating acrophobia and claustrophobia. This pilot study, which holds the promise of a future where mental health is more accessible and effective, explores the feasibility of leveraging transdisciplinary collaboration among specialists to create a safe, accessible, and effective VRET solution. Methods: We conducted a Delphi heuristic approach involving bioethicists, neuroscientists, and tech developers. Second, we reviewed the existing psychological theories and therapeutic strategies for addressing phobias in VR. Third, we conceptualized a thematic analysis-derived framework for a safe, adaptive-gamified free exposure to virtual reality acrophobia and claustrophobia (SAFEvR ACT). Finally, we provide an overview of the iterative improvements made during 12 workshops and 76 weekly briefings on developmental implementations. Results: We developed the SAFEvR ACT into a proof-of-concept application freely deployed on the MentalVerse app platform. Our safety-focused approach can benefit from prevalidation perspectives within future randomized control trials. Conclusions: The resulting application derived from the SAFEvR ACT framework represents a blueprint to counter the current lack of iVR mental health uptake by offering a free VRET alternative. Future research should aim towards developing similar free platforms to lessen mental health burdens and gather quantitative data. We conclude with a call to action to researchers to fine-tune our current approach and take a stand for free digital mental health within MentalVeRse.app. Full article

Phobias are a type of anxiety disorder characterized by severe fear of objects and situations. In recent years, virtual reality exposure therapy has emerged as a safer and more convenient method of treating phobias, with the same rate of success as classical therapy, the in vivo exposure to stimuli. Following extensive research concerning the available technologies and after studying the state of the art in the field, we developed the PhoVR (Phobia therapy through Virtual Reality) system during a 2-year long project that involved the participation of a technical university, a biology faculty, and an industry partner specialized in designing 3D applications. Our final prototype incorporates scenarios for acrophobia, claustrophobia, and fear of public speaking therapy, in which the user is required to perform gamified tasks and navigate virtual reality environments with biophysical data acquisition (electrodermal activity and heart rate), automatic anxiety level classification, biofeedback integrated into the scenes’ elements, the dynamic adaptation of the virtual environments, and relaxation techniques made available at any moment. The control panel is an application dedicated to psychotherapists for managing patients’ profiles and therapy sessions. The feedback obtained in a qualitative survey with subjects and psychotherapists who evaluated the prototype validated the system and provided suggestions for refinement. Full article

Acrophobia (fear of heights), a prevalent psychological disorder, elicits profound fear and evokes a range of adverse physiological responses in individuals when exposed to heights, which will lead to a very dangerous state for people in actual heights. In this paper, we explore the behavioral influences in terms of movements in people confronted with virtual reality scenes of extreme heights and develop an acrophobia classification model based on human movement characteristics. To this end, we used wireless miniaturized inertial navigation sensors (WMINS) network to obtain the information of limb movements in the virtual environment. Based on these data, we constructed a series of data feature processing processes, proposed a system model for the classification of acrophobia and non-acrophobia based on human motion feature analysis, and realized the classification recognition of acrophobia and non-acrophobia through the designed integrated learning model. The final accuracy of acrophobia dichotomous classification based on limb motion information reached 94.64%, which has higher accuracy and efficiency compared with other existing research models. Overall, our study demonstrates a strong correlation between people’s mental state during fear of heights and their limb movements at that time. Full article

This research applies exposure to the visual appearance technology of virtual reality (VR). The motivation for this research is to generate a creative intervention by using regular smartphone devices and implementing them in VR using Google Cardboard as a medium visual display for exposure therapy at high altitudes. The VR application in this research is called acrophobia immersive virtual exposure (AIVE), which utilizes the Unity3D software to develop this treatment therapy application. The utilization of exposure therapy was carried out as a therapeutic medium for acrophobia sufferers. A commissioner was given to measure the usefulness of applications and devices in the VR environment created, and as many as 20 users had tested the VR device. The existing questionnaire was revised to develop a questionnaire for acrophobia sufferers, which was then used as an index measurement in the VR environment. The research is expected to be used to design a simulator and as a therapeutic medium using immersive VR devices in future studies. Full article

This study examined user engagement with ZeroPhobia, a self-guided app-based virtual reality (VR) Cognitive Behavior Therapy for acrophobia symptoms using cardboard VR viewers. Dutch acrophobic adults (n = 96) completed assessments at baseline and immediately following treatment. Primary outcome measures were the Acrophobia Questionnaire (AQ) and the Igroup Presence Questionnaire (IPQ). Usage data consisted of number of VR sessions practiced, practice time, and fear ratings directly after practicing. Results show that of the 66 participants who played at least one level, the majority continued to finish all levels, spending on average 24.4 min in VR. Self-reported fear consistently decreased between the start and finish of levels. Post-test AQ scores depended quadratically on time spent in VR. Higher pre-test AQ scores were significantly associated with subjective anxiety after the first level and a reduction of post-test AQ scores, but not with number of sessions, suggesting it might be more beneficial to play one level for a longer time period instead of practicing many VR levels. Results also show an optimum exposure level at which increasing practice time does not result in increased benefit. Self-guided VR acrophobia treatment is effective and leads to consistent reductions in self-reported anxiety both between levels and after treatment. Most participants progressed effectively to the highest self-exposure level, despite the absence of a therapist. Full article

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. Full article

In this paper, we investigate various machine learning classifiers used in our Virtual Reality (VR) system for treating acrophobia. The system automatically estimates fear level based on multimodal sensory data and a self-reported emotion assessment. There are two modalities of expressing fear ratings: the 2-choice scale, where 0 represents relaxation and 1 stands for fear; and the 4-choice scale, with the following correspondence: 0—relaxation, 1—low fear, 2—medium fear and 3—high fear. A set of features was extracted from the sensory signals using various metrics that quantify brain (electroencephalogram—EEG) and physiological linear and non-linear dynamics (Heart Rate—HR and Galvanic Skin Response—GSR). The novelty consists in the automatic adaptation of exposure scenario according to the subject’s affective state. We acquired data from acrophobic subjects who had undergone an in vivo pre-therapy exposure session, followed by a Virtual Reality therapy and an in vivo evaluation procedure. Various machine and deep learning classifiers were implemented and tested, with and without feature selection, in both a user-dependent and user-independent fashion. The results showed a very high cross-validation accuracy on the training set and good test accuracies, ranging from 42.5% to 89.5%. The most important features of fear level classification were GSR, HR and the values of the EEG in the beta frequency range. For determining the next exposure scenario, a dominant role was played by the target fear level, a parameter computed by taking into account the patient’s estimated fear level. Full article