PTSD in the Wild: A Video Database for Studying Post-Traumatic Stress Disorder Recognition in Unconstrained Environments
Moctar Abdoul Latif Sawadogo, Furkan Pala, Gurkirat Singh, Imen Selmi,, Pauline Puteaux, Alice Othmani

TL;DR
This paper introduces a new diverse video dataset for automatic PTSD diagnosis in unconstrained environments, providing benchmarks and evaluating deep learning methods for PTSD recognition.
Contribution
The paper presents the first publicly available video dataset for PTSD detection in natural settings, along with benchmarks and a deep learning approach for automatic diagnosis.
Findings
Deep learning approach achieves promising results.
Dataset exhibits high variability in conditions and demographics.
Provides a new resource for PTSD research in real-world scenarios.
Abstract
POST-traumatic stress disorder (PTSD) is a chronic and debilitating mental condition that is developed in response to catastrophic life events, such as military combat, sexual assault, and natural disasters. PTSD is characterized by flashbacks of past traumatic events, intrusive thoughts, nightmares, hypervigilance, and sleep disturbance, all of which affect a person's life and lead to considerable social, occupational, and interpersonal dysfunction. The diagnosis of PTSD is done by medical professionals using self-assessment questionnaire of PTSD symptoms as defined in the Diagnostic and Statistical Manual of Mental Disorders (DSM). In this paper, and for the first time, we collected, annotated, and prepared for public distribution a new video database for automatic PTSD diagnosis, called PTSD in the wild dataset. The database exhibits "natural" and big variability in acquisition…
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Taxonomy
TopicsPosttraumatic Stress Disorder Research
