Description:

Presenter: 
Shrikanth Narayanan, Ph.D.
University of Southern California, Los Angeles, CA
Signal Analysis and Interpretation Laboratory

Topic: Deriving multimodal behavioral informatics for health applications

Abstract:

The convergence of sensing, communication and computing technologies is allowing capture and access to data, in diverse forms and modalities, in ways that were unimaginable even a few years ago. These include data that afford the analysis and interpretation of multimodal cues of verbal and non-verbal human behavior to facilitate human behavioral research and its translational applications in healthcare. These data not only carry crucial information about a person’s intent, identity and trait but also underlying attitudes, emotions and other mental state constructs. Automatically capturing these cues, although vastly challenging, offers the promise of not just efficient data processing but in creating tools for discovery that enable hitherto unimagined scientific insights, and means for supporting diagnostics and interventions. Recent computational approaches that have leveraged judicious use of both data and knowledge have yielded significant advances in this regard, for example in deriving rich, context-aware information from multimodal signal sources including human speech, language, and videos of behavior. These are even complemented and integrated with data about human brain and body physiology. This talk will focus on some of the advances and challenges in gathering such data and creating algorithms for machine processing of such cues. It will highlight some of our ongoing efforts in Behavioral Signal Processing (BSP)—technology and algorithms for quantitatively and objectively understanding typical, atypical and distressed human behavior—with a specific focus on communicative, affective and social behavior. The talk will illustrate Behavioral Informatics applications of these techniques that contribute to quantifying higher-level, often subjectively described, human behavior in a domain-sensitive fashion. Examples will be drawn from mental health and well being realms such as Autism Spectrum Disorders, Couple therapy, Depression and Addiction counseling.

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About PSMG:

Ce-PIM‘s Prevention Science and Methodology Group (PSMG) is a virtual network of more than 480 empirical researchers and methodologists aimed to advance the field of prevention science and support the implementation of evidence-based prevention programs. The PSMG grand rounds are now conducted virtually over the internet, allowing the members to view, question, and comment live from their own computer with leading scientists and methodologists at no cost. Access to live presentations is restricted to PSMG members. However, PSMG presentations are recorded and will be publicly accessible on our website two weeks after the presentation date on the archive page.

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