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/ Information Innovation Office (I2O)

Detection and Computational Analysis of Psychological Signals (DCAPS)

The Detection and Computational Analysis of Psychological Signals (DCAPS) program aims to develop novel analytical tools to assess psychological status of warfighters in the hopes of improving psychological health awareness and enabling them to seek timely help. DCAPS tools will be developed to analyze patterns in everyday behaviors to detect subtle changes associated with post-traumatic stress disorder, depression and suicidal ideation. In particular, DCAPS hopes to advance the state-of-the-art in extraction and analysis of 'honest signals' from a wide variety of sensory data inherent in daily social interactions. DCAPS is not aimed at providing an exact diagnosis, but at providing a general metric of psychological health.

Program Manager: Mr. Wade Shen

Contact: wade.shen@darpa.mil

The content below has been generated by organizations that are partially funded by DARPA; the views and conclusions contained therein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of DARPA or the U.S. Government.

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Last updated: November 13, 2015

TeamProjectCategoryCodeDescriptionLicense
Cogito Health VetGuard PTSD, depression, indicators, health informatics daniel.ragsdale@darpa.mil VetGuard is part of a mobile-enabled "stepped-care" platform that provides three major technical components: Cogito dialog (shows voice interactions between two interactants, off-the-shelf), Cogito central (datasets of large human interactions, finding targets of interventions, commercially available in 2 months), and Cogito companion, which includes VetGuard (TRL6). (C++/Java/Python) GPR
Poulin Holdings Durkheim System PTSD, depression, indicators, health informatics daniel.ragsdale@darpa.mil Durkheim is a medically-validated suicidality classifier with a system infrastructure designed to support clinicians, patients, and potential patients. The system provides real-time monitoring of mobile and social information for risks associated with suicidality and suicide ideation. (C++/Java/PHP/HTML) UGPR
BBN (publications), Raytheon (publications) MINAT PTSD, depression, indicators, health informatics daniel.ragsdale@darpa.mil Medical Informatics and Analytics Toolkit (MINAT) was created to: 1) Code distress indicators (includes 75 element codebook), 2) Apply to multi-genre, multi-modal communication, 3) Show evidence for decisions, and 4) Triage for suicidal/homicidal ideation run as a deployable web service. UGPR
BBN (publications), Intific, ABM NeuroAnalysis PTSD, depression, indicators, health informatics daniel.ragsdale@darpa.mil The NeuroAnalysis system is designed as a low-cost, configurable tool for multi-modal stimuli presentation and synchronized biometric data collection. (C++/C#/ActionScript/Lua/Python) GPR
USC (publications), ICT (publications) SimSensei PTSD, depression, indicators, health informatics daniel.ragsdale@darpa.mil SimSensei seeks to enable a new generation of clinical decision support tools and interactive virtual agent-based healthcare dissemination/delivery systems that are able to recognize and identify psychological distress from multimodal signals. SimSensei uses user-state which can also be used to create long-term patient profiles that help assess change over time. GPR
TeamTitleLink
USC, ICT User-State Sensing for Virtual Health Agents and TeleHealth Applications
USC, ICT Automatic Behavior Descriptors for Psychological Disorder Analysis
USC, ICT Crowdsourcing Micro-Level Multimedia Annotations: The Challenges of Evaluation and Interface
USC, ICT FAAST-R: Defining a Core Mechanic for Designing Gestural Interfaces
USC, ICT A Mixed-Initiative Conversational Dialogue System for Healthcare
USC, ICT Unobtrusive Measurement of Subtle Nonverbal Behaviors with the Microsoft Kinect
BBN, Raytheon Automatic Detection of Psychological Distress Indicators from Online Forum Posts
BBN, Raytheon Model-based Parametric Features for Emotion Recognition from Speech
BBN, Raytheon Ensemble of SVM Trees for Multimodal Emotion Recognition
BBN, Raytheon Emotion Recognition using Acoustic and Lexical Features
USC, ICT SimSensei Kiosk: A Virtual Human Interviewer for Healthcare Decision Support
USC, ICT Verbal Indicators of Psychological Distress in Interactive Dialogue with a Virtual Human
USC, ICT It's Only a Computer: The Impact of Human-agent Interaction in Clinical Interviews
USC, ICT The Distress Analysis Interview Corpus of Human and Computer Interviews
USC, ICT Investigating Voice Quality as a Speaker-Independent Indicator of Depression and PTSD
USC, ICT Audiovisual Behavior Descriptors for Depression Assessment
USC, ICT Context-based Signal Descriptors of Heart-rate Variability for Anxiety Assessment
BBN, Raytheon Robust EEG Emotion Classification Using Segment Level Decision Fusion
USC, ICT Automatic Nonverbal Behavior Indicators of Depression and PTSD: Exploring Gender Differences
USC, ICT Perception Markup Language: Towards a Standardized Representation of Perceived Nonverbal Behaviors
USC, ICT Adapting User Interfaces for Gestural Interaction with the Flexible Action and Articulated Skeleton Toolkit
BBN, Raytheon Compact Unsupervised EEG Response Representation for Emotion Recognition

Software

Publications