Nonverbal social withdrawal in depression: Evidence from manual and automatic analyses
Open accessAbstract
The relationship between nonverbal behavior and severity of depression was investigated by following depressed participants over the course of treatment and video recording a series of clinical interviews. Facial expressions and head pose were analyzed from video using manual and automatic systems. Both systems were highly consistent for FACS action units (AUs) and showed similar effects for change over time in depression severity. When symptom severity was high, participants made fewer affiliative facial expressions (AUs 12 and 15) and more non-affiliative facial expressions (AU 14). Participants also exhibited diminished head motion (i.e., amplitude and velocity) when symptom severity was high. These results are consistent with the Social Withdrawal hypothesis: that depressed individuals use nonverbal behavior to maintain or increase interpersonal distance. As individuals recover, they send more signals indicating a willingness to affiliate. The finding that automatic facial expression analysis was both consistent with manual coding and revealed the same pattern of findings suggests that automatic facial expression analysis may be ready to relieve the burden of manual coding in behavioral and clinical science.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Depression recognition from FEs is a very important application in analysis of psychological distress.
“Depression recognition from FEs is a very important application in analysis of psychological distress [53], [54], [55].”
From Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (2016) · cites this paper as [53]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,841 · see citing works
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398 · see citing works
LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918 · see citing works
An analysis of variance test for normality (complete samples)
SHAPIRO, S. S., & WILK, M. B. (1965) · Biometrika · doi:10.1093/biomet/52.3-4.591 · Cited by 23,480 · see citing works
Intraclass correlations: Uses in assessing rater reliability.
Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 23,433 · see citing works
An introduction to ROC analysis
Fawcett, T. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.10.010 · Cited by 21,879 · see citing works
Statistical Methods for Rates and Proportions
Fleiss, J. L., Levin, B., & Paik, M. C. (2003) · Wiley Series in Probability and Statistics · doi:10.1002/0471445428 · Cited by 18,646 · see citing works
Individual Comparisons by Ranking Methods
Wilcoxon, F. (1945) · Biometrics Bulletin · doi:10.2307/3001968 · Cited by 15,354 · see citing works
Zhang, Q., Wang, C., Zheng, M., Li, Y., Li, J., Zhang, L., Shang, X., & Yan, C. (2014) · Cerebrovascular Diseases · doi:10.1159/000369778 · Cited by 11,609 · see citing works
Projections of Global Mortality and Burden of Disease from 2002 to 2030
Mathers, C. D., & Loncar, D. (2006) · PLoS Medicine · doi:10.1371/journal.pmed.0030442 · Cited by 11,386 · see citing works
Development of a Rating Scale for Primary Depressive Illness
Hamilton, M. (1967) · British Journal of Social and Clinical Psychology · doi:10.1111/j.2044-8260.1967.tb00530.x · Cited by 8,410 · see citing works
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
Belkin, M., & Niyogi, P. (2003) · Neural Computation · doi:10.1162/089976603321780317 · Cited by 7,562 · see citing works
Bower, G. H. (1981) · American Psychologist · doi:10.1037//0003-066x.36.2.129 · Cited by 5,798 · see citing works
Cootes, T. F., Edwards, G. J., & Taylor, C. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927467 · Cited by 5,409 · see citing works
Depression. Clinical, Experimental, and Theoretical Aspects.
(1968) · Annals of Internal Medicine · doi:10.7326/0003-4819-68-2-502 · Cited by 5,232 · see citing works
A Practical Guide to Support Vector Classication
Hsu, C., Chang, C.-C., & Lin, C. (2008) · Cited by 5,070 · see citing works
Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications.
Clark, L. A., & Watson, D. (1991) · Journal of Abnormal Psychology · doi:10.1037//0021-843x.100.3.316 · Cited by 4,602 · see citing works
Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications
Clark, L. A., & Watson, D. (1991) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.100.3.316 · Cited by 4,601 · see citing works
Bower, G. H. (1981) · American Psychologist · doi:10.1037/0003-066x.36.2.129 · Cited by 4,154 · see citing works
Statistical Methods for Rates and Proportions, 2nd ed
GROVE, W. A. (1981) · American Journal of Psychiatry · doi:10.1176/ajp.138.12.1644-a · Cited by 3,756 · see citing works
Diagnostic and Statistical Manual of Mental Disorders
Raber, G., & Spokas, M. (2024) · doi:10.4135/9781071886229.n145 · Cited by 2,806 · see citing works
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797 · see citing works
Kotov, R., Gamez, W., Schmidt, F., & Watson, D. (2010) · Psychological Bulletin · doi:10.1037/a0020327 · Cited by 2,677 · see citing works
Statistical Methods for Rates and Proportions.
Plewis, I., & Fleiss, J. L. (1982) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2982107 · Cited by 1,753 · see citing works
Active Appearance Models Revisited
Matthews, I., & Baker, S. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029666.37597.d3 · Cited by 1,538 · see citing works
Toward an Interactional Description of Depression
Coyne, J. C. (1976) · Psychiatry · doi:10.1080/00332747.1976.11023874 · Cited by 1,506 · see citing works
Interpersonal Psychotherapy Of Depression
Klerman, G. L. (1984) · Medical Entomology and Zoology · Cited by 1,315 · see citing works
Human facial expression: an evolutionary view
(1995) · Choice Reviews Online · doi:10.5860/choice.32-3890 · Cited by 1,275 · see citing works
The Tie That Binds? Coherence Among Emotion Experience, Behavior, and Physiology.
Mauss, I. B., Levenson, R. W., McCarter, L., Wilhelm, F. H., & Gross, J. J. (2005) · Emotion · doi:10.1037/1528-3542.5.2.175 · Cited by 1,201 · cited 1× · see citing works
“Dissociations between expressive behavior and physiology have been observed in other contexts [58]; depression may be another.”
BackgroundA Survey of Dimension Reduction Techniques
Fodor, I. K. (2002) · doi:10.2172/15002155 · Cited by 1,109 · see citing works
First, M. B., Spitzer, R. L., Gibbon, M., & Williams, J. B. W. (1997) · American Psychiatric Press eBooks · Cited by 983 · see citing works
Consequences of commitment to and disengagement from incentives.
Klinger, E. (1975) · Psychological Review · doi:10.1037/h0076171 · Cited by 969 · see citing works
A meta-analysis of emotional reactivity in major depressive disorder
Bylsma, L. M., Morris, B. H., & Rottenberg, J. (2008) · Clinical Psychology Review · doi:10.1016/j.cpr.2007.10.001 · Cited by 933 · see citing works
Nesse, R. M. (2000) · Archives of General Psychiatry · doi:10.1001/archpsyc.57.1.14 · Cited by 891 · see citing works
Interpersonal Psychotherapy of Depression
Rush, A. J. (1985) · American Journal of Psychiatry · doi:10.1176/ajp.142.11.1381 · Cited by 831 · see citing works
Li, S. Z., & Jain, A. K. (2005) · Springer eBooks · doi:10.1007/b138828 · Cited by 791 · see citing works
Embarrassment: its distinct form and appeasement functions
Keltner, D., & Buswell, B. N. (1997) · Psychological Bulletin · doi:10.1037/0033-2909.122.3.250 · Cited by 751 · see citing works
Neurobehavioral Aspects of Affective Disorders
Depue, R. A., & Iacono, W. G. (1989) · Annual Review of Psychology · doi:10.1146/annurev.ps.40.020189.002325 · Cited by 722 · see citing works
Emotion context insensitivity in major depressive disorder
Rottenberg, J., Gross, J. J., & Gotlib, I. H. (2005) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.114.4.627 · Cited by 654 · see citing works
Facial expressions of emotion influence interpersonal trait inferences
Knutson, B. (1996) · Journal of Nonverbal Behavior · doi:10.1007/bf02281954 · Cited by 644 · see citing works
Depression—Clinical, Experimental, and Theoretical Aspects
Strasburger, L. H. (1968) · Psychosomatic Medicine · doi:10.1097/00006842-196811000-00018 · Cited by 595 · see citing works
Social skills deficits associated with depression
Segrin, C. G. (2000) · Clinical Psychology Review · doi:10.1016/s0272-7358(98)00104-4 · Cited by 594 · see citing works
Treatment and prevention of depression
Hollon, S. D., Thase, M. E., & Markowitz, J. C. (2002) · Psychological Science in the Public Interest · doi:10.1111/1529-1006.00008 · Cited by 511 · see citing works
Allen, N. B., & Badcock, P. B. T. (2003) · Psychological Bulletin · doi:10.1037/0033-2909.129.6.887 · Cited by 494 · see citing works
Detecting depression from facial actions and vocal prosody
Cohn, J. F., Kruez, T. S., Matthews, I., Yang, Y., Nguyen, M. H., Padilla, M. T., Zhou, F., & De la Torre, F. (2009) · 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops · doi:10.1109/acii.2009.5349358 · Cited by 494 · see citing works
Self-citationAutomatic Recognition of Facial Actions in Spontaneous Expressions
Bartlett, M. S., Littlewort, G. C., Frank, M. G., Lainscsek, C., Fasel, I. R., & Movellan, J. R. (2006) · Journal of Multimedia · doi:10.4304/jmm.1.6.22-35 · Cited by 468 · see citing works
Emotional experience and expression in schizophrenia and depression.
Berenbaum, H., & Oltmanns, T. F. (1992) · Journal of Abnormal Psychology · doi:10.1037//0021-843x.101.1.37 · Cited by 431 · see citing works
Tian, Y., Takeo Kanade, A., & Cohn, J. F. (2005) · Springer eBooks · doi:10.1007/0-387-27257-7_12 · Cited by 407 · see citing works
Self-citationDecreased responsiveness to reward in depression
Henriques, J. B., & Davidson, R. J. (2000) · Cognition & Emotion · doi:10.1080/02699930050117684 · Cited by 399 · see citing works
Rottenberg, J. A., Kasch, K. L., Gross, J. J., & Gotlib, I. H. (2002) · Emotion · doi:10.1037/1528-3542.2.2.135 · Cited by 360 · see citing works
Emotional experience and expression in schizophrenia and depression
Berenbaum, H., & Oltmanns, T. F. (1992) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.101.1.37 · Cited by 345 · see citing works
Hess, U., Blairy, S., & Kleck, R. E. (2000) · Journal of Nonverbal Behavior · doi:10.1023/a:1006623213355 · Cited by 340 · see citing works
The functional relation between depression and problematic interpersonal behavior.
Youngren, M. A., & Lewinsohn, P. M. (1980) · Journal of Abnormal Psychology · doi:10.1037//0021-843x.89.3.333 · Cited by 328 · see citing works
Toward Practical Smile Detection
Whitehill, J., Littlewort, G. C., Fasel, I., Bartlett, M. S., & Movellan, J. R. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.42 · Cited by 310 · see citing works
(2009) · Springer eBooks · doi:10.1007/978-0-387-73003-5_2171 · Cited by 269 · see citing works
Sloman, L. (2003) · Journal of Affective Disorders · doi:10.1016/s0165-0327(02)00116-7 · Cited by 230 · see citing works
Diminished response to pleasant stimuli by depressed women
Sloan, D. M., Strauss, M. E., & Wisner, K. L. (2001) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.110.3.488 · Cited by 229 · see citing works
Takeo Kanade, A. (2005) · Lecture notes in computer science · doi:10.1007/11564386_1 · Cited by 226 · see citing works
Who may frown and who should smile? Dominance, affiliation, and the display of happiness and anger
Heß, U., Adams, R. B., & Kleck, R. E. (2005) · Cognition & Emotion · doi:10.1080/02699930441000364 · Cited by 226 · see citing works
Studies in dyadic communication
Marzillier, J. S. (1973) · Behaviour Research and Therapy · doi:10.1016/0005-7967(73)90129-0 · Cited by 194 · see citing works
Sloan (1997) · doi:10.1016/s0165-0327(97)00097-9 · Cited by 163 · see citing works
Trémeau, F., Malaspina, D., Duval, F., Corrêa, H., Hager-Budny, M., Coin-Bariou, L., Macher, J.-P., & Gorman, J. M. (2004) · American Journal of Psychiatry · doi:10.1176/appi.ajp.162.1.92 · Cited by 157 · see citing works
The Analysis of Movement Behavior During the Clinical Interview
Freedman, N. (1972) · Elsevier eBooks · doi:10.1016/b978-0-08-015867-9.50012-5 · Cited by 155 · see citing works
Automatic behavior descriptors for psychological disorder analysis
Scherer, S., Stratou, G., Mahmoud, M., Boberg, J., Gratch, J., Rizzo, A., & Morency, L.-P. (2013) · 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG) · doi:10.1109/fg.2013.6553789 · Cited by 147 · see citing works
The Interactional Theory of Depression: A Meta-Analysis of the Research Literature
Segrin, C. G., & Dillard, J. P. (1992) · Journal of Social and Clinical Psychology · doi:10.1521/jscp.1992.11.1.43 · Cited by 144 · see citing works
(1989) · Cited by 141 · see citing works
Gehricke, J.-G., & Shapiro, D. (2000) · Psychiatry Research · doi:10.1016/s0165-1781(00)00168-2 · Cited by 136 · see citing works
Facial expression of emotions in borderline personality disorder and depression
Renneberg, B., Heyn, K., Gebhard, R., & Bachmann, S. (2005) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/j.jbtep.2005.05.002 · Cited by 127 · see citing works
Can body expressions contribute to automatic depression analysis?
Joshi, J., Goecke, R., Parker, G. B., & Breakspear, M. J. (2013) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2013.6553796 · Cited by 123 · see citing works
A framework for automated measurement of the intensity of non-posed Facial Action Units
Mahoor, M. H., Cadavid, S., Messinger, D. S., & Cohn, J. F. (2009) · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2009.5204259 · Cited by 115 · see citing works
Self-citationFacial expressivity in the course of schizophrenia and depression
Gäebel, W., & W�lwer, W. (2004) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-004-0510-5 · Cited by 114 · see citing works
Algorithms for manifold learning
Cayton, L. (2005) · Cited by 101 · see citing works
Impact of depression on response to comedy: A dynamic facial coding analysis.
Reed, L. I., Sayette, M. A., & Cohn, J. F. (2007) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.116.4.804 · Cited by 100 · see citing works
Self-citationHandbook of psychiatric measures, 2nd ed.
Rush, A. J., First, M. B., & Blacker, D. (2008) · Cited by 100 · see citing works
Some Nonverbal Aspects of Depression and Schizophrenia Occurring during the Interview
Jones, I. H., & Pansa, M. C. (1979) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-197907000-00002 · Cited by 87 · see citing works
Chentsova-Dutton, Y. E., Tsai, J. L., & Gotlib, I. H. (2010) · Cultural Diversity & Ethnic Minority Psychology · doi:10.1037/a0017562 · Cited by 81 · see citing works
Matsumoto, D., & Ekman, P. (2008) · Scholarpedia · doi:10.4249/scholarpedia.4237 · Cited by 79 · see citing works
Cross-cultural detection of depression from nonverbal behaviour
Alghowinem, S., Goecke, R., Cohn, J. F., Wagner, M., Parker, G. B., & Breakspear, M. J. (2015) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2015.7163113 · Cited by 77 · see citing works
Self-citationIntegrative views of motivation, cognition and emotion
Corr, P. J. (1995) · Personality and Individual Differences · doi:10.1016/0191-8869(95)90021-7 · Cited by 76 · see citing works
Analyzing nonverbal behavior in depression.
Fisch, H., Frey, S., & Hirsbrunner, H.-P. (1983) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.92.3.307 · Cited by 76 · see citing works
The Ethological Approach to the Assessment of Depressive Disorders
FOSSI, L., Faravelli, C., & PAOLI, M. (1984) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-198406000-00004 · Cited by 73 · see citing works
Gender differences in depression:
Troisi, A., & Moles, A. (1999) · Journal of Psychiatric Research · doi:10.1016/s0022-3956(98)00064-8 · Cited by 71 · see citing works
Social Functioning and Facial Emotional Expression in Neurological and Psychiatric Disorders
Brozgold, A. Z., Borod, J. C., Martin, C., Pick, L. H., Alpert, M., & Welkowitz, J. (1998) · Applied Neuropsychology · doi:10.1207/s15324826an0501_2 · Cited by 64 · see citing works
In the Pursuit of Effective Affective Computing: The Relationship Between Features and Registration
Chew, S. W., Lucey, P., Lucey, S., Saragih, J., Cohn, J. F., Matthews, I., & Sridharan, S. (2012) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2012.2194485 · Cited by 64 · see citing works
Self-citationEthological Studies in Animals and Man, Their Use in Psychiatry
Dixon, A. K., Fisch, H. U., Huber, C. G., & Walser, A. (1989) · Pharmacopsychiatry · doi:10.1055/s-2007-1014624 · Cited by 62 · see citing works
Computer-based analysis of facial action in schizophrenic and depressed patients
Schneider, F. W., Heimann, H., Himer, W., Huss, D., Mattes, R., & Adam, B. (1990) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/bf02189974 · Cited by 58 · see citing works
A Controlled Quantitative Study of Facial Expression in Parkinsonʼs Disease and Depression
Katsikitis, M., & Pilowsky, I. (1991) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-199111000-00006 · Cited by 56 · see citing works
Cohn, J. F., & Sayette, M. A. (2010) · Behavior Research Methods · doi:10.3758/brm.42.4.1079 · Cited by 55 · see citing works
Self-citationMajor Depression: Behavioral Markers of Depression and Recovery
SCHELDE, J. T. M. (1998) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-199803000-00001 · Cited by 55 · see citing works
Major Depression: Behavioral Parameters of Depression and Recovery
SCHELDE, J. T. M. (1998) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-199803000-00002 · Cited by 54 · see citing works
Zhu, Y., la Torre, F. D., Cohn, J. F., & Zhang, Y. (2011) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.10 · Cited by 53 · see citing works
Self-citationThe effects of depression on the emotional responses of Spanish-speaking Latinas.
Tsai, J. L., Pole, N., LEVENSON, R. W., & Muñoz, R. F. (2003) · Cultural Diversity & Ethnic Minority Psychology · doi:10.1037/1099-9809.9.1.49 · Cited by 50 · see citing works
Mergl, R. (2004) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.2004.037127 · Cited by 41 · see citing works
The effects of alcohol on the emotional displays of Whites in interracial groups.
Fairbairn, C. E., Sayette, M. A., Levine, J. M., Cohn, J. F., & Creswell, K. G. (2013) · Emotion · doi:10.1037/a0030934 · Cited by 33 · see citing works
Self-citationDynamic cascades with bidirectional bootstrapping for spontaneous facial action unit detection
Zhu, Y., la Torre, F. D., Cohn, J. F., & Zhang, Y. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349603 · Cited by 30 · see citing works
Self-citationPolygraphic Evaluation of Laughing and Smiling in Schizophrenic and Depressive Patients
Sakamoto, S., NAMETA, K., Kawasaki, T., Yamashita, K., & Shimizu, A. (1997) · Perceptual and Motor Skills · doi:10.2466/pms.1997.85.3f.1291 · Cited by 19 · see citing works
Expression, emotion, neither, or both?
Frijda, N. H. (1995) · Cognition & Emotion · doi:10.1080/02699939508408986 · Cited by 16 · see citing works
Temporal coordination of head motion in couples with history of interpersonal violence
Hammal, Z., Bailie, T. E., Cohn, J. F., George, D. T., Saraghi, J., Nuevo, J., & Lucey, S. (2013) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2013.6553793 · Cited by 9 · see citing works
Self-citation
Flagged first, then by citations
1 of the 99 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
A review of depression and suicide risk assessment using speech analysis
Cummins, N., Scherer, S. J., Krajewski, J., Schnieder, S., Epps, J., & Quatieri, T. F. (2015) · Speech Communication · doi:10.1016/j.specom.2015.03.004 · Cited by 1,007 · see citing works
BP4D-Spontaneous: a high-resolution spontaneous 3D dynamic facial expression database
Zhang, X., Yin, L., Cohn, J. F., Canavan, S., Reale, M., Horowitz, A., Liu, P., & Girard, J. M. (2014) · Image and Vision Computing · doi:10.1016/j.imavis.2014.06.002 · Cited by 745 · see citing works
Self-citationCorneanu, C. A., Simon, M. O., Cohn, J. F., & Guerrero, S. E. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2515606 · Cited by 527 · see citing works
Self-citationDu Preez, A., Onorato, D., Eiben, I., Musaelyan, K., Egeland, M., Zunszain, P. A., Fernandes, C., Thuret, S., & Pariante, C. M. (2021) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2020.07.015 · Cited by 285 · see citing works
Visually Interpretable Representation Learning for Depression Recognition from Facial Images
Zhou, X., Jin, K., Shang, Y., & Guo, G. (2018) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2828819 · Cited by 273 · see citing works
Automated Depression Diagnosis Based on Deep Networks to Encode Facial Appearance and Dynamics
Zhu, Y. M., Shang, Y., Shao, Z., & Guo, G. (2017) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2650899 · Cited by 258 · see citing works
Deep learning for depression recognition with audiovisual cues: A review
He, L., Niu, M., Tiwari, P., Marttinen, P., Su, R., Jiang, J., Guo, C., Wang, H., Ding, S., Wang, Z., et al. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.10.012 · Cited by 270 · see citing works
Automatic Assessment of Depression Based on Visual Cues: A Systematic Review
Pampouchidou, A., Simos, P. G., Kostas Marias, A., Mériaudeau, F., Yang, F., Pediaditis, M., & Tsiknakis, M. (2017) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2724035 · Cited by 224 · see citing works
Dynamic Multimodal Measurement of Depression Severity Using Deep Autoencoding
Dibeklioğlu, H., Hammal, Z., & Cohn, J. F. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2676878 · Cited by 196 · see citing works
Self-citationAutomatic depression recognition using CNN with attention mechanism from videos
He, L., Chan, J. C.-W., & Wang, Z. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.10.015 · Cited by 179 · see citing works
Video-Based Depression Level Analysis by Encoding Deep Spatiotemporal Features
Jazaery, M. A., & Guo, G. (2018) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2870884 · Cited by 158 · see citing works
Spectral Representation of Behaviour Primitives for Depression Analysis
Song, S., Jaiswal, S., Shen, L., & Valstar, M. (2020) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2020.2970712 · Cited by 149 · see citing works
Decision Tree Based Depression Classification from Audio Video and Language Information
Yang, L., Jiang, D., He, L., Pei, E., Oveneke, M. C., & Hichem Sahli, B. (2016) · International Workshop on Audio/Visual Emotion Challenge (AVEC) · doi:10.1145/2988257.2988269 · Cited by 148 · see citing works
Davies, H. A., Wolz, I., Leppänen, J., Fernández‐Aranda, F., Schmidt, U. H., & Tchanturia, K. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.02.015 · Cited by 142 · see citing works
Automated Depression Diagnosis Based on Facial Dynamic Analysis and Sparse Coding
Wen, L., Li, X., Guo, G., & Zhu, Y. M. (2015) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2414392 · Cited by 141 · see citing works
Song, S., Shen, L., & Valstar, M. (2018) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2018.00032 · Cited by 133 · see citing works
Scherer, S. J., Lucas, G., Gratch, J. S., Rizzo, A., & Morency, L. (2015) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2015.2440264 · Cited by 122 · see citing works
A comprehensive survey on automatic facial action unit analysis
Zhi, R., Liu, M., & Zhang, D. (2019) · The Visual Computer · doi:10.1007/s00371-019-01707-5 · Cited by 127 · see citing works
Gassner, L., Geretsegger, M., & Mayer-Ferbas, J. (2021) · European Journal of Public Health · doi:10.1093/eurpub/ckab042 · Cited by 125 · see citing works
Analysis of acoustic space variability in speech affected by depression
Cummins, N., Sethu, V., Epps, J., Schnieder, S., & Krajewski, J. (2015) · Speech Communication · doi:10.1016/j.specom.2015.09.003 · Cited by 120 · see citing works
Integrating Deep and Shallow Models for Multi-Modal Depression Analysis—Hybrid Architectures
Yang, L., Jiang, D., & Hichem Sahli, B. (2018) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2870398 · Cited by 121 · see citing works
Assessment of late-life depression via self-report measures: a review
Balsamo, M., Cataldi, F., Carlucci, L., Padulo, C., & Fairfield, B. (2018) · Clinical Interventions in Aging · doi:10.2147/cia.s178943 · Cited by 121 · see citing works
Multimodal Prediction of Affective Dimensions and Depression in Human-Computer Interactions
Gupta, R., Malandrakis, N., Xiao, B., Guha, T., Segbroeck, M. V., Black, M., Potamianos, A., & Narayanan, S. S. (2014) · International Workshop on Audio/Visual Emotion Challenge (AVEC) · doi:10.1145/2661806.2661810 · Cited by 110 · see citing works
He, L., Jiang, D., & Hichem Sahli, B. (2018) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2018.2877129 · Cited by 113 · see citing works
Zou, B., Han, J., Wang, Y., Liu, R., Zhao, S., Feng, L., Lyu, X., & Ma, H. (2022) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2022.3181210 · Cited by 114 · see citing works
CARMA: Software for Continuous Affect Rating and Media Annotation
Girard, J. M. (2014) · Journal of Open Research Software · doi:10.5334/jors.ar · Cited by 108 · see citing works
Self-citationGeorgescu, A. L., Koeroglu, S., Hamilton, A. F. D. C., Vogeley, K. T., Falter‐Wagner, C. M., & Tschacher, W. (2020) · Molecular Autism · doi:10.1186/s13229-019-0305-1 · Cited by 100 · see citing works
Advancing the Assessment of Dynamic Psychological Processes
Wright, A. G. C., & Hopwood, C. J. (2016) · Assessment · doi:10.1177/1073191116654760 · Cited by 95 · see citing works
Yasin, S., Othmani, A., Raza, I., & Hussain, S. A. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106741 · Cited by 90 · see citing works
Wang, J. Z., Zhao, S., Wu, C., Adams, R. B., Newman, M. G., Shafir, T., & Tsachor, R. P. (2023) · Proceedings of the IEEE · doi:10.1109/jproc.2023.3273517 · Cited by 98 · see citing works
The Effortless Assessment of Risk States (EARS) Tool: An Interpersonal Approach to Mobile Sensing
Lind, M. N., Byrne, M. L., Wicks, G., Smidt, A. M., & Allen, N. B. (2018) · JMIR Mental Health · doi:10.2196/10334 · Cited by 84 · see citing works
Shumye, S., Belayneh, Z., & Mengistu, N. (2019) · Health and Quality of Life Outcomes · doi:10.1186/s12955-019-1233-7 · Cited by 79 · see citing works
Facial Depression Recognition by Deep Joint Label Distribution and Metric Learning
Zhou, X., Wei, Z., Xu, M., Qu, S., & Guo, G. (2020) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2020.3022732 · Cited by 80 · see citing works
A Primer on Observational Measurement
Girard, J. M., & Cohn, J. F. (2016) · Assessment · doi:10.1177/1073191116635807 · Cited by 74 · see citing works
Self-citationHossain, S., Umer, S., Rout, R. K., & Tanveer, M. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.109997 · Cited by 77 · see citing works
A Cross-modal Review of Indicators for Depression Detection Systems
Morales, M. R., Scherer, S. J., & Levitan, R. (2017) · Workshop on Computational Linguistics and Clinical Psychology (CLPsych) · doi:10.18653/v1/w17-3101 · Cited by 71 · see citing works
Spontaneous facial expression in unscripted social interactions can be measured automatically
Girard, J. M., Cohn, J. F., Jeni, L. A., Sayette, M. A., & De la Torre, F. (2015) · Behavior Research Methods · doi:10.3758/s13428-014-0536-1 · Cited by 69 · see citing works
Self-citationPRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression
Liu, Z., Yuan, X., Li, Y., Shangguan, Z., Zhou, L., & Hu, B. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106589 · Cited by 69 · see citing works
Multimodal Sensing for Depression Risk Detection: Integrating Audio, Video, and Text Data
Zhang, Z., Zhang, S., Ni, D., Wei, Z., Yang, K., Jin, S., Huang, G., Liang, Z., Zhang, L., Li, L., et al. (2024) · Sensors · doi:10.3390/s24123714 · Cited by 68 · see citing works
A temporally piece-wise fisher vector approach for depression analysis
Dhall, A., & Goecke, R. (2015) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2015.7344580 · Cited by 67 · see citing works
Zou, L., Wang, T., Herold, F., Ludyga, S., Liu, W., Zhang, Y., Healy, S., Zhang, Z., Kuang, J., Taylor, A., et al. (2022) · International Journal of Clinical and Health Psychology · doi:10.1016/j.ijchp.2022.100337 · Cited by 68 · see citing works
Detecting Depression Severity by Interpretable Representations of Motion Dynamics
Kacem, A., Hammal, Z., Daoudi, M., & Jeffrey, C. (2018) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2018.00116 · Cited by 64 · see citing works
Self-citationMultimodal depression recognition with dynamic visual and audio cues
He, L., Jiang, D., & Hichem Sahli, B. (2015) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2015.7344581 · Cited by 63 · see citing works
Automated audiovisual depression analysis
Girard, J. M., & Cohn, J. F. (2015) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2014.12.010 · Cited by 62 · see citing works
Self-citationJiang, Z., Harati, S., Crowell, A., Mayberg, H. S., Nemati, S., & Clifford, G. D. (2021) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2020.3010472 · Cited by 60 · see citing works
Sequential fusion of facial appearance and dynamics for depression recognition
Chen, Q., Chaturvedi, I., Ji, S., & Cambria, E. (2021) · Pattern Recognition Letters · doi:10.1016/j.patrec.2021.07.005 · Cited by 61 · see citing works
Zhou, Y., Han, W., Yao, X., Xue, J., Li, Z., & Li, Y. (2023) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2023.104562 · Cited by 60 · see citing works
Large-Scale Observational Evidence of Cross-Cultural Differences in Facial Behavior
McDuff, D., Girard, J. M., & Kaliouby, R. E. (2017) · Journal of Nonverbal Behavior · doi:10.1007/s10919-016-0244-x · Cited by 60 · see citing works
Self-citationFacial expression video analysis for depression detection in Chinese patients
Wang, Q., Yang, H., & Yu, Y. (2018) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2018.11.003 · Cited by 59 · see citing works
LQGDNet: A Local Quaternion and Global Deep Network for Facial Depression Recognition
Shang, Y., Pan, Y., Jiang, X., Shao, Z., Guo, G., Liu, T., & Ding, H. (2021) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2021.3139651 · Cited by 58 · see citing works
Automatic nonverbal behavior indicators of depression and PTSD: the effect of gender
Stratou, G., Scherer, S. J., Gratch, J. S., & Morency, L. (2014) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-014-0161-4 · Cited by 57 · see citing works
Xu, J., Güneş, H., Kusumam, K., Valstar, M., & Song, S. (2024) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2024.3415770 · Cited by 55 · see citing works
Multimodal assessment of depression from behavioral signals
Cohn, J. F., Cummins, N., Epps, J., Goecke, R., Joshi, J., & Scherer, S. J. (2018) · ACM eBooks · doi:10.1145/3107990.3108004 · Cited by 55 · see citing works
Self-citationCurrent Directions in Personality Science and the Potential for Advances through Computing
Wright, A. G. C. (2014) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2014.2332331 · Cited by 52 · see citing works
He, L., Guo, C., Tiwari, P., Su, R., Pandey, H. M., & Dang, W. (2021) · International Journal of Intelligent Systems · doi:10.1002/int.22704 · Cited by 57 · see citing works
Zaman, A., Zhang, B., Hoque, M. E., Silenzio, V., & Kautz, H. (2020) · JMIR Mental Health · doi:10.2196/24012 · Cited by 50 · see citing works
Action unit analysis enhanced facial expression recognition by deep neural network evolution
Zhi, R., Zhou, C., Li, T., Liu, S., & Jin, Y. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.03.036 · Cited by 51 · see citing works
Prediction of depression symptoms in individual subjects with face and eye movement tracking
Stolicyn, A., Steele, J. D., & Seriès, P. (2020) · Psychological Medicine · doi:10.1017/s0033291720003608 · Cited by 50 · see citing works
Head movements and postures as pain behavior
Werner, P., Al-Hamadi, A. K., Limbrecht-Ecklundt, K., Walter, S., & Traue, H. C. (2018) · PLoS ONE · doi:10.1371/journal.pone.0192767 · Cited by 45 · see citing works
Estimating smile intensity: A better way
Girard, J. M., Cohn, J. F., & De la Torre, F. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2014.10.004 · Cited by 44 · see citing works
Self-citationGeneralized Two-Stage Rank Regression Framework for Depression Score Prediction from Speech
Cummins, N., Sethu, V., Epps, J., Williamson, J. R., Quatieri, T. F., & Krajewski, J. (2017) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2766145 · Cited by 44 · see citing works
Automated screening for distress: A perspective for the future
Rana, R. K., Latif, S., Gururajan, R., Gray, A. D., Mackenzie, G., Humphris, G. M., & Dunn, J. C. (2019) · European Journal of Cancer Care · doi:10.1111/ecc.13033 · Cited by 45 · see citing works
Tao, C., Zhang, G.-W., Sun, W.-J., Huang, J. J., Zhang, L. I., & Tao, H. W. (2024) · Nature Communications · doi:10.1038/s41467-024-52727-2 · Cited by 42 · see citing works
AFFDEX 2.0: A Real-Time Facial Expression Analysis Toolkit
Bishay, M., Preston, K., Strafuss, M., Page, G., Turcot, J., & Mavadati, M. (2023) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg57933.2023.10042673 · Cited by 40 · see citing works
Dyadic Behavior Analysis in Depression Severity Assessment Interviews
Scherer, S. J., Hammal, Z., Yang, Y., Morency, L., & Cohn, J. F. (2014) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/2663204.2663238 · Cited by 40 · see citing works
Self-citationInvestigating Facial Behavior Indicators of Suicidal Ideation
Laksana, E., Baltrušaitis, T., Morency, L., & Pestian, J. P. (2017) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2017.96 · Cited by 39 · see citing works
Emotion Network Analysis During COVID-19 Quarantine ‐ A Longitudinal Study
Martín-Brufau, R., Suso‐Ribera, C., & Berná, F. J. C. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.559572 · Cited by 39 · see citing works
Yadav, S., Chauhan, J., Sain, J. P., Thirunarayan, K., Sheth, A., & Schumm, J. A. (2020) · International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.61 · Cited by 44 · see citing works
Detecting depression in speech: Comparison and combination between different speech types
Long, H., Guo, Z., Wu, X., Hu, B. X., Liu, Z., & Cai, H. (2017) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2017.8217802 · Cited by 38 · see citing works
Ali, R., Hoque, E., Duberstein, P., Schubert, L., Razavi, S. Z., Kane, B., Silva, C., Daks, J. S., Huang, M., & Van Orden, K. (2021) · The American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2020.11.004 · Cited by 38 · see citing works
Depression Severity Estimation from Multiple Modalities
Stepanov, E. A., Lathuilière, S., Chowdhury, S. A., Ghosh, A., Vieriu, R.-L., Sebe, N., & Riccardi, G. (2018) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2018.8531119 · Cited by 39 · see citing works
Detecting depression based on facial cues elicited by emotional stimuli in video
Hu, B., Tao, Y., & Yang, M. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107457 · Cited by 36 · see citing works
How much training data for facial action unit detection?
Girard, J. M., Cohn, J. F., Jeni, L. A., Lucey, S., & la Torre, F. D. (2015) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2015.7163106 · Cited by 37 · see citing works
Self-citationDigital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review
Ettore, É., Müller, P., Hinze, J., Riemenschneider, M. J., Benoît, M., Giordana, B., Postin, D., Hurlemann, R., Lecomte, A., Musiol, M., et al. (2022) · JMIR Mental Health · doi:10.2196/37225 · Cited by 36 · see citing works
Facial expression of positive emotions in individuals with eating disorders
Dapelo, M. M., Hart, S., Hale, C., Morris, R. G., Lynch, T. R., & Tchanturia, K. (2015) · Psychiatry Research · doi:10.1016/j.psychres.2015.08.019 · Cited by 35 · see citing works
Human vision inspired feature extraction for facial expression recognition
Sadeghi, H., & Raie, A. A. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-07863-z · Cited by 35 · see citing works
Bipolar Disorder Recognition with Histogram Features of Arousal and Body Gestures
Yang, L., Li, Y., Chen, H., Jiang, D., Oveneke, M. C., & Hichem Sahli, B. (2018) · doi:10.1145/3266302.3266308 · Cited by 33 · see citing works
Harati, S., Crowell, A. L., Huang, Y., Mayberg, H. S., & Nemati, S. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2930604 · Cited by 33 · see citing works
Bekhbat, M., Mukhara, D., Dozmorov, M. G., Stansfield, J. C., Benusa, S. D., Hyer, M. M., Rowson, S. A., Kelly, S. D., Qin, Z. S., Dupree, J. L., et al. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-00970-2 · Cited by 34 · see citing works
Othmani, A., & Zeghina, A. O. (2022) · Healthcare Analytics · doi:10.1016/j.health.2022.100090 · Cited by 33 · see citing works
Bastin, M., Luyckx, K., Raes, F., & Bijttebier, P. (2021) · Journal of Youth and Adolescence · doi:10.1007/s10964-021-01412-4 · Cited by 32 · see citing works
Passively-sensed Behavioral Correlates of Discrimination Events in College Students
Sefidgar, Y. S., Seo, W., Kuehn, K. S., Althoff, T., Browning, A., Riskin, E. A., Nurius, P. S., Dey, A. K., & Mankoff, J. C. (2019) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3359216 · Cited by 29 · see citing works
Bodily Behaviors in Social Interaction
Balážia, M., Müller, P., Tánczos, Á. L., von Liechtenstein, A., & Brémond, F. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548363 · Cited by 30 · see citing works
Deep Learning for Facial Action Unit Detection Under Large Head Poses
Tősér, Z., Jeni, L. A., Lörincz, A., & Cohn, J. F. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-49409-8_29 · Cited by 29 · see citing works
Self-citationLandmark based head pose estimation benchmark and method
Werner, P., Saxen, F., & Al-Hamadi, A. K. (2017) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2017.8297015 · Cited by 29 · see citing works
Spatiotemporal Attention Based Deep Neural Networks for Emotion Recognition
Lee, J., Kim, S., Kiim, S., & Sohn, K. (2018) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2018.8461920 · Cited by 29 · see citing works
Cheng, Y., & Meng, J. (2021) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.258 · Cited by 32 · see citing works
On the review of image and video-based depression detection using machine learning
Ashraf, A., Gunawan, T. S., Riza, B. S., Haryanto, E. V., & Janin, Z. (2020) · Indonesian Journal of Electrical Engineering and Computer Science · doi:10.11591/ijeecs.v19.i3.pp1677-1684 · Cited by 31 · see citing works
Disbudding affects use of a shelter provided to group-housed dairy calves
Gingerich, K. N., Choulet, V., & Miller-Cushon, E. K. (2020) · Journal of Dairy Science · doi:10.3168/jds.2020-18267 · Cited by 28 · see citing works
Behavioral Sentiment Analysis of Depressive States
Esposito, A. A., Raimo, G., Maldonato, M. N., Vogel, C. M., Conson, M., & Cordasco, G. (2020) · IEEE International Conference on Cognitive Infocommunications · doi:10.1109/coginfocom50765.2020.9237856 · Cited by 28 · see citing works
Wang, L., Wang, C., Li, C., Murai, T., Bai, Y., Song, Z., Zhang, S., Zhang, Q., Huang, Y., Bi, X., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01933-3 · Cited by 33 · see citing works
“Additionally, depression patients exhibit slow audio rates and increased negative facial expressions 15 .”
Spontaneous Facial Expressions Reveal New Action Units for the Sad Experiences
Namba, S., Kagamihara, T., Miyatani, M., & Nakao, T. (2017) · Journal of Nonverbal Behavior · doi:10.1007/s10919-017-0251-6 · Cited by 26 · see citing works
Implementing Gender-Dependent Vowel-Level Analysis for Boosting Speech-Based Depression Recognition
Vlasenko, B., Sagha, H., Cummins, N., & Schuller, B. W. (2017) · Interspeech (USB) · doi:10.21437/interspeech.2017-887 · Cited by 27 · see citing works
A naturalistic method to test depression: Anticipation of play
Burke, C. J., Modlińska, K., Mauro, M. H., Aleksandrova, L. R., Pellis, S. M., Phillips, A. G., & Euston, D. R. (2020) · Behavioural Brain Research · doi:10.1016/j.bbr.2020.112975 · Cited by 24 · see citing works
Probabilistic acoustic volume analysis for speech affected by depression
Cummins, N., Sethu, V., Epps, J., & Krajewski, J. (2014) · Interspeech (USB) · doi:10.21437/interspeech.2014-311 · Cited by 24 · see citing works
Historical Heterogeneity Predicts Smiling: Evidence from Large-Scale Observational Analyses
Girard, J. M., & McDuff, D. (2017) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2017.135 · Cited by 24 · see citing works
Self-citationA Summarization of the Visual Depression Databases for Depression Detection
Ashraf, A., Gunawan, T. S., Rahman, F. D. A., Kartiwi, M., Ismail, N., & Ulfiah (2020) · International Conference on Wireless and Telematics (ICWT) · doi:10.1109/icwt50448.2020.9243625 · Cited by 24 · see citing works
Objective Methods for Reliable Detection of Concealed Depression
Solomon, C., Valstar, M., Morriss, R. K., & Crowe, J. A. (2015) · Frontiers in ICT · doi:10.3389/fict.2015.00005 · Cited by 24 · see citing works
Enhanced memory for negative social information in borderline personality disorder.
Niedtfeld, I., Renkewitz, F., Mädebach, A., Hillmann, K., Kleindienst, N., Schmahl, C., & Schulze, L. (2020) · Journal of Abnormal Psychology · doi:10.1037/abn0000540 · Cited by 22 · see citing works
A review on depression detection and diagnoses based on visual facial cues
Nasser, S. A., Hashim, I. A., & Ali, W. H. (2020) · International Conference on Engineering Technology and its Applications (IICETA) · doi:10.1109/iiceta50496.2020.9318860 · Cited by 22 · see citing works
- Authors
- Girard, J. M., Cohn, J. F., Mahoor, M. H., Mavadati, S. M., Hammal, Z., & Rosenwald, D. P.
- Affiliations
- University of Pittsburgh (US)
- University of Denver (US)
- Carnegie Mellon University (US)
- Corresponding author
- Girard, Jeffrey M.
- Venue
- Image and Vision Computing
- Publisher
- Elsevier BV
- Published
- 2014-10
- Volume
- 32
- Issue
- 10
- Pages
- 641-647
- ISSN
- 0262-8856 (ISSN-L)
- PMC
- PMC4217695
- OpenAlex
- W2096976598
- Cited by
- 255
- References
- 99
- Citations by year
- 2026: 15 · 2025: 21 · 2024: 19 · 2023: 31 · 2022: 21 · 2021: 19 · 2020: 28 · 2019: 19 · 2018: 30 · 2017: 16 · 2016: 10 · 2015: 14 · 2014: 12
- FWCI
- 16.26
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Image and Vision Computing (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Commons - DU (University of Denver) (submittedVersion)
- Funders
- National Institutes of Health (MH61435, MH65376, MH096951)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- depression, nonverbal behavior, social withdrawal, facial expressions, head orientation, facial action units, manual coding, affiliative behavior, head movement, interpersonal distance, treatment response, video analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review