Automatic Nonverbal Behavior Indicators of Depression and PTSD: Exploring Gender Differences (bibtex)
by Stratou, Giota, Scherer, Stefan, Gratch, Jonathan and Morency, Louis-Philippe
Abstract:
In this paper, we show that gender plays an important role in the automatic assessment of psychological conditions such as depression and post-traumatic stress disorder (PTSD). We identify a directly interpretable and intuitive set of predictive indicators, selected from three general categories of nonverbal behaviors: affect, expression variability and motor variability. For the analysis, we introduce a semi-structured virtual human interview dataset which includes 53 video recorded interactions. Our experiments on automatic classification of psychological conditions show that a gender-dependent approach significantly improves the performance over a gender agnostic one.
Reference:
Automatic Nonverbal Behavior Indicators of Depression and PTSD: Exploring Gender Differences (Stratou, Giota, Scherer, Stefan, Gratch, Jonathan and Morency, Louis-Philippe), In Affective Computing and Intelligent Interaction, IEEE, 2013.
Bibtex Entry:
@inproceedings{stratou_automatic_2013,
	address = {Geneva, Switzerland},
	title = {Automatic {Nonverbal} {Behavior} {Indicators} of {Depression} and {PTSD}: {Exploring} {Gender} {Differences}},
	isbn = {978-0-7695-5048-0},
	shorttitle = {Automatic {Nonverbal} {Behavior} {Indicators} of {Depression} and {PTSD}},
	url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6681422},
	doi = {10.1109/ACII.2013.31},
	abstract = {In this paper, we show that gender plays an important role in the automatic assessment of psychological conditions such as depression and post-traumatic stress disorder (PTSD). We identify a directly interpretable and intuitive set of predictive indicators, selected from three general categories of nonverbal behaviors: affect, expression variability and motor variability. For the analysis, we introduce a semi-structured virtual human interview dataset which includes 53 video recorded interactions. Our experiments on automatic classification of psychological conditions show that a gender-dependent approach significantly improves the performance over a gender agnostic one.},
	booktitle = {Affective {Computing} and {Intelligent} {Interaction}},
	publisher = {IEEE},
	author = {Stratou, Giota and Scherer, Stefan and Gratch, Jonathan and Morency, Louis-Philippe},
	month = sep,
	year = {2013},
	keywords = {Virtual Humans, UARC},
	pages = {147--152}
}
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