Physiological feature extraction and fusion to assist in the diagnosis of post-traumatic stress disorder

摘要

Post-traumatic stress disorder (PTSD), and other anxiety disorders, are diagnosed via clinical interviews in which subjective self-reports of traumatic events and associated experiences are discussed with a mental health professional. The system and methods described herein classify and diagnose patients as suffering from anxiety disorders by measuring objective physiological measures, such as inter-heartbeat interval and skin conductance. The system measures various physiological measures and then extracts features from the physiological measures. A diagnosis is then made by classifying the extracted features using one of a neural network, Bayesian network, or a support vector machine.