Automatic detection of facial expressions during the Cyberball paradigm in Borderline Personality Disorder: a pilot study

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dc.contributor.affiliationDirección de Servicios Clínicos, Instituto Nacional de Psiquiatría "Ramón de la Fuente Muñiz", Mexico City, Mexico.
dc.contributor.emailalexiaro@rocketmail.com
dc.creatorArango-de-Montis, Ivánes_ES
dc.creatorReyes-Soto, Adrianaes_ES
dc.creatorRosales-Lagarde, Alejandraes_ES
dc.creatorEraña-Díaz, Marta-Liliaes_ES
dc.creatorVázquez-Mendoza, Enriquees_ES
dc.creatorRodríguez-Delgado, Andréses_ES
dc.creatorMuñoz-Delgado, Jairoes_ES
dc.creatorVázquez-Mendoza, Isaaces_ES
dc.creatorRodriguez-Torres, Erika Elizabethes_ES
dc.date2024
dc.date.accessioned2026-01-29T18:36:58Z
dc.date.accessioned2026-03-27T15:34:02Z
dc.date.available2026-01-29T18:36:58Z
dc.date.issued2024
dc.date.published2024
dc.descriptionBorderline Personality Disorder (BPD) symptoms include inappropriate control of anger and severe emotional dysregulation after rejection in daily life. Nevertheless, when using the Cyberball paradigm, a tossing game to simulate social exclusion, the seven basic emotions (happiness, sadness, anger, surprise, fear, disgust, and contempt) have not been exhaustively tracked out. It was hypothesized that these patients would show anger, contempt, and disgust during the condition of exclusion versus the condition of inclusion. When facial emotions are automatically detected by Artificial Intelligence, "blending", -or a mixture of at least two emotions- and "masking", -or showing happiness while expressing negative emotions- may be most easily traced expecting higher percentages during exclusion rather than inclusion. Therefore, face videos of fourteen patients diagnosed with BPD (26 ± 6 years old), recorded while playing the tossing game, were analyzed by the FaceReader software. The comparison of conditions highlighted an interaction for anger: it increased during inclusion and decreased during exclusion. During exclusion, the masking of surprise; i.e., displaying happiness while feeling surprised, was significantly more expressed. Furthermore, disgust and contempt were inversely correlated with greater difficulties in emotion regulation and symptomatology, respectively. Therefore, the automatic detection of emotional expressions during both conditions could be useful in rendering diagnostic guidelines in clinical scenarios.es_ES
dc.formatPDFes_ES
dc.identifierOE01SC25es_ES
dc.identifier.doi10.3389/fpsyt.2024.1354762
dc.identifier.issn1664-0640
dc.identifier.organizacionInstituto Nacional de Psiquiatría Ramón de la Fuente Muñiz
dc.identifier.placeSuiza
dc.identifier.urihttps://doi.org/10.3389/fpsyt.2024.1354762
dc.identifier.urihttps://repositorio.inprf.gob.mx/handle/123456789/8518
dc.language.isoenges_ES
dc.publisherFrontiers Research Foundationes_ES
dc.relation28:15:1354762
dc.relation.jnabreviadoFRONT PSYCHIATRY
dc.relation.journalFrontiers in Psychiatry
dc.rightsAcceso Cerradoes_ES
dc.subject.kwArea under the curve
dc.subject.kwBorderline personality disorder
dc.subject.kwCyberball paradigm
dc.subject.kwEmotions
dc.subject.kwFace
dc.subject.kwNon-verbal expression
dc.subject.kwPattern analysis
dc.subject.kwSocial exclusion
dc.titleAutomatic detection of facial expressions during the Cyberball paradigm in Borderline Personality Disorder: a pilot studyes_ES
dc.typeArtículoes_ES

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