Deep Learning for Emotion Recognition in VR-EBT

In my research, I delve into the transformative potential of deep learning algorithms in enhancing Virtual Reality Exposure-Based Treatment (VR-EBT) for Post Traumatic Stress Disorder (PTSD). The central objective is to automate the intricate emotion recognition process, thereby elevating the efficacy and accessibility of VR-EBT.

Utilizing a multimodal physiological framework, I employed deep neural networks to analyze a comprehensive dataset of physiological recordings and emotional responses. The empirical results demonstrate deep neural networks' feasibility and superior performance in emotion recognition tasks. These findings pave the way for a new paradigm in mental health treatment, particularly in exposure-based therapies.