Phobia Detection Using Virtual Reality

Abstract

Phobias are intense, irrational fears that can significantly impact an individual's daily life. Traditional methods of diagnosing phobias rely on self-reports and clinical interviews, which can be subjective and time-consuming. This project, Virtual Phobia Detection, aims to develop an advanced system that utilizes virtual reality (VR) and artificial intelligence (AI) to detect and assess phobias in individuals. The system immerses users in controlled virtual environments designed to simulate various phobia-inducing scenarios, such as confined spaces, or social interactions. Biometric sensors, including heart rate monitor capture physiological responses, while the system analyzes behavioral and emotional reactions. Machine learning models process this data to classify the severity of the phobia and generate reports. By integrating VR, this project enhances the accuracy and objectivity of phobia detection, offering a more immersive and data-driven approach to mental health assessment. The Virtual Phobia Detection system has potential applications in clinical psychology, therapy, and research, helping professionals design tailored interventions for patients suffering from phobias