Computational-based behavior analysis and peripheral psychophysiology (bibtex)
by Khooshabeh, Peter, Scherer, Stefan, Oiumette, Brett, Ryan, William S., Lance, Brent J. and Gratch, Jonathan
Abstract:
Computational-based behavior analysis aims to automatically identify, characterize, model, and synthesize multimodal nonverbal behavior within both human–machine as well as machine-mediated human–human interaction. It uses state-of-the-art machine learning algorithms to track human nonverbal and verbal information, such as facial expressions, gestures, and posture, as well as what and how a person speaks. The emerging technology from this field of research is relevant for a wide range of interactive and social applications, including health care and education. The characterization and association of nonverbal behavior with underlying clinical conditions, such as depression or posttraumatic stress, could have significant benefits for treatments and the overall efficiency of the health care system.
Reference:
Computational-based behavior analysis and peripheral psychophysiology (Khooshabeh, Peter, Scherer, Stefan, Oiumette, Brett, Ryan, William S., Lance, Brent J. and Gratch, Jonathan), In Advances in Computational Psychophysiology, 2015.
Bibtex Entry:
@article{khooshabeh_computational-based_2015,
	title = {Computational-based behavior analysis and peripheral psychophysiology},
	url = {http://www.sciencemag.org/sites/default/files/custom-publishing/documents/CP_Supplement_Final_100215.pdf},
	abstract = {Computational-based behavior analysis aims to automatically identify, characterize, model, and synthesize multimodal nonverbal behavior within both human–machine as well as machine-mediated human–human interaction. It uses state-of-the-art machine learning algorithms to track human nonverbal and verbal information, such as facial expressions, gestures, and posture, as well as what and how a person speaks. The emerging technology from this field of research is relevant for a wide range of interactive and social applications, including health care and education. The characterization and association of nonverbal behavior with underlying clinical conditions, such as depression or posttraumatic stress, could have significant benefits for treatments and the overall efficiency of the health care system.},
	journal = {Advances in Computational Psychophysiology},
	author = {Khooshabeh, Peter and Scherer, Stefan and Oiumette, Brett and Ryan, William S. and Lance, Brent J. and Gratch, Jonathan},
	month = oct,
	year = {2015},
	keywords = {Virtual Humans, UARC, ARL, DoD},
	pages = {34--36}
}
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