Technologies for Assessing Behavioral and Cognitive Markers of Suicide Risk
DOD Proposal # : PT140188
Title : Technologies for Assessing Behavioral and Cognitive Markers of Suicide Risk
In the current project, we propose innovative methods for investigating the causes and development of suicide risk among members of the National Guard and their family members by examining the behavioral, cognitive, and emotional dynamics that occur within military couples, thereby addressing these three knowledge gaps in suicide prevention. We will employ novel Behavioral Signal Processing technologies that allow scaling up and systematizing data collections thus enabling expanded observational windows through in-situ observations of both spouses, and expansion of the pertinent information available. Our proposed research strategy is designed to optimize our ability to achieve this scientific aim as well as to lay the foundation for an internet-based platform that can be used by concerned spouses to assess suicide risk from home on an as-needed basis. To achieve these objectives, we will partner with the National Center for Veterans Studies, a non-profit research and advocacy organization with strong ties to the local military and veteran communities.
Dr. Georgiou leads this effort along with Drs. Baucom, Univ. of Utah and Narayanan.
Quantitative Observational Practice in Family Studies
Transform observational behavior analysis through computational framework
Model emotionally-rich human interactions by signal processing and machine learning methods
Alleviate the tedium of manual annotation, offer new analysis capabilities and empower the mental health experts
Shrikanth S. Narayanan and Panayiotis G. Georgiou, Behavioral Signal Processing: Deriving Human Behavioral Informatics from Speech and Language (2013), in: Proceedings of IEEE, 101:5(1203 - 1233)
Matthew P. Black, Athanasios Katsamanis, Brian Baucom, Chi-Chun Lee, Adam Lammert, Andrew Christensen, Panayiotis G. Georgiou and Shrikanth S. Narayanan, Toward automating a human behavioral coding system for married couples' interactions using speech acoustic features (2013), in: Speech Communication, 55:1(1--21)