Multi-Modal Prediction Of Ptsd And Stress Indicators

Post-traumatic stress disorder (PTSD) is an anxiety disorder that affects a large population and that is currently diagnosed mostly through subject interviews and manual analysis of self-reported symptoms and of subject behavior. However, most PTSD cases are believed to go underdiagnosed and undertreated. We present a multi-modal system for computer-aided diagnosis of PTSD and stress that requires no clinician interview and relies principally in the elicitation of multimodal neurophysiological responses to audio-visual stimuli. We conduct a thorough evaluation of the discriminative power of the modalities involved (electro encephalography, galvanic skin-response, electrocardiography, head motion and speech), type of stimuli presented (audio, images, audio-and-images and video), and emotions evoked (positive, negative, and trauma-specific) between PTSD subjects and high and low-stress control groups. Our analysis indicates that the multi-modal prediction from the elicitation of trauma-specific emotions from images and audio is a promising approach to computer-aided diagnosis.