Document Type

Book Chapter

Publication Date




Publication Title

Medicine Meets Virtual Reality 19






Comprehensive evaluation of PTSD includes diagnostic interviews, self-report testing, and physiological reactivity measures. It is often difficult and costly to diagnose PTSD due to patient access and the variability in symptoms presented. Additionally, potential patients are often reluctant to seek help due to the stigma associated with the disorder. A voice-based automated system that is able to remotely screen individuals at high risk for PTSD and monitor their symptoms during treatment has the potential to make great strides in alleviating the barriers to cost effective PTSD assessment and progress monitoring. In this paper we present a voice-based automated Tele-PTSD Monitor (TPM) system currently in development, designed to remotely screen, and provide assistance to clinicians in diagnosing PTSD. The TPM system can be accessed via a Public Switched Telephone Network (PSTN) or the Internet. The acquired voice data is then sent to a secure server to invoke the PTSD Scoring Engine (PTSD-SE) where a PTSD mental health score is computed. If the score exceeds a predefined threshold, the system will notify clinicians (via email or short message service) for confirmation and/or an appropriate follow-up assessment and intervention. The TPM system requires only voice input and performs computer-based automated PTSD scoring, resulting in low cost and easy field-deployment. The concept of the TPM system was supported using a limited dataset with an average detection accuracy of up to 95.88%.


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Reprinted from Medicine Meets Virtual Reality 19, 173, Roger Xu, Gang Mei, Guangfan Zhang, Pan Gao, Timothy Judkins, Michael Cannizzaro, and Jiang Li, A voice-based automated system for PTSD screening and monitoring, 552-558, 2012, with permission from IOS Press.

Original Publication Citation

Xu, R., Mei, G., Zhang, G., Gao, P., Judkins, T., Cannizzaro, M., & Li, J. (2012). A voice-based automated system for PTSD screening and monitoring. In J. D. Westwood, S. W. Westwood, L. Felländer-Tsai, R. S. Haluck, R. A. Robb, S. Senger, & K. G. Vosburgh (Eds.), Medicine meets virtual reality 19 (pp. 552-558). IOS Press.


0000-0003-0091-6986 (Li)