Developing and Validating a Facial Emotion Recognition Task With Graded Intensity

Assessment ◽  
2022 ◽  
pp. 107319112110680
Author(s):  
Trevor F. Williams ◽  
Niko Vehabovic ◽  
Leonard J. Simms
Keyword(s):  
Psychometric Properties ◽  
Emotion Recognition ◽  
Internal Consistency ◽  
Recognition Task ◽  
Reliability And Validity ◽  
Facial Emotion Recognition ◽  
Self Report ◽  
Facial Emotion ◽  
Validity Measures ◽  
Emotional Face

Facial emotion recognition (FER) tasks are often digitally altered to vary expression intensity; however, such tasks have unknown psychometric properties. In these studies, an FER task was developed and validated—the Graded Emotional Face Task (GEFT)—which provided an opportunity to examine the psychometric properties of such tasks. Facial expressions were altered to produce five intensity levels for six emotions (e.g., 40% anger). In Study 1, 224 undergraduates viewed subsets of these faces and labeled the expressions. An item selection algorithm was used to maximize internal consistency and balance gender and ethnicity. In Study 2, 219 undergraduates completed the final GEFT and a multimethod battery of validity measures. Finally, in Study 3, 407 undergraduates oversampled for borderline personality disorder (BPD) completed the GEFT and a self-report BPD measure. Broad FER scales (e.g., overall anger) demonstrated evidence of reliability and validity; however, more specific subscales (e.g., 40% anger) had more variable psychometric properties. Notably, ceiling/floor effects appeared to decrease both internal consistency and limit external validity correlations. The findings are discussed from the perspective of measurement issues in the social cognition literature.

scholarly journals Facial Emotion Recognition Predicts Alexithymia Using Machine Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Nima Farhoumandi ◽  
Sadegh Mollaey ◽  
Soomaayeh Heysieattalab ◽  
Mostafa Zarean ◽  
Reza Eyvazpour
Keyword(s):  
Machine Learning ◽  
Emotion Recognition ◽  
Recognition Task ◽  
Influential Factors ◽  
Facial Emotion Recognition ◽  
Self Report ◽  
Facial Emotion ◽  
Support Vector ◽  
Learning Models ◽  
Machine Learning Models

Objective. Alexithymia, as a fundamental notion in the diagnosis of psychiatric disorders, is characterized by deficits in emotional processing and, consequently, difficulties in emotion recognition. Traditional tools for assessing alexithymia, which include interviews and self-report measures, have led to inconsistent results due to some limitations as insufficient insight. Therefore, the purpose of the present study was to propose a new screening tool that utilizes machine learning models based on the scores of facial emotion recognition task. Method. In a cross-sectional study, 55 students of the University of Tabriz were selected based on the inclusion and exclusion criteria and their scores in the Toronto Alexithymia Scale (TAS-20). Then, they completed the somatization subscale of Symptom Checklist-90 Revised (SCL-90-R), Beck Anxiety Inventory (BAI) and Beck Depression Inventory-II (BDI-II), and the facial emotion recognition (FER) task. Afterwards, support vector machine (SVM) and feedforward neural network (FNN) classifiers were implemented using K-fold cross validation to predict alexithymia, and the model performance was assessed with the area under the curve (AUC), accuracy, sensitivity, specificity, and F1-measure. Results. The models yielded an accuracy range of 72.7–81.8% after feature selection and optimization. Our results suggested that ML models were able to accurately distinguish alexithymia and determine the most informative items for predicting alexithymia. Conclusion. Our results show that machine learning models using FER task, SCL-90-R, BDI-II, and BAI could successfully diagnose alexithymia and also represent the most influential factors of predicting it and can be used as a clinical instrument to help clinicians in diagnosis process and earlier detection of the disorder.

scholarly journals Lighting for pedestrians: Does multi-tasking affect the performance of typical pedestrian tasks?

2021 ◽  
pp. 147715352110026
Author(s):  
Y Mao ◽  
S Fotios
Keyword(s):  
Emotion Recognition ◽  
Recognition Task ◽  
Obstacle Detection ◽  
Detection Task ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Impaired Performance ◽  
Lighting Conditions ◽  
Multiple Tasks ◽  
Visual Tasks

Obstacle detection and facial emotion recognition are two critical visual tasks for pedestrians. In previous studies, the effect of changes in lighting was tested for these as individual tasks, where the task to be performed next in a sequence was known. In natural situations, a pedestrian is required to attend to multiple tasks, perhaps simultaneously, or at least does not know which of several possible tasks would next require their attention. This multi-tasking might impair performance on any one task and affect evaluation of optimal lighting conditions. In two experiments, obstacle detection and facial emotion recognition tasks were performed in parallel under different illuminances. Comparison of these results with previous studies, where these same tasks were performed individually, suggests that multi-tasking impaired performance on the peripheral detection task but not the on-axis facial emotion recognition task.

Affective functioning and social cognition in Noonan syndrome

2011 ◽  
Vol 42 (2) ◽  
pp. 419-426 ◽  
Author(s):  
E. Wingbermühle ◽  
J. I. M. Egger ◽  
W. M. A. Verhoeven ◽  
I. van der Burgt ◽  
R. P. C. Kessels
Keyword(s):  
Social Cognition ◽  
Emotion Recognition ◽  
Noonan Syndrome ◽  
Heart Defects ◽  
Genetic Disorder ◽  
Recognition Task ◽  
Well Being ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Clinical Group

BackgroundNoonan syndrome (NS) is a common genetic disorder, characterized by short stature, facial dysmorphia, congenital heart defects and a mildly lowered IQ. Impairments in psychosocial functioning have often been suggested, without, however, systematic investigation in a clinical group. In this study, different aspects of affective processing, social cognition and behaviour, in addition to personal well-being, were assessed in a large group of patients with NS.MethodForty adult patients with NS were compared with 40 healthy controls, matched with respect to age, sex, intelligence and education level. Facial emotion recognition was measured with the Emotion Recognition Task (ERT), alexithymia with both the 20-item Toronto Alexithymia Scale (TAS-20) and the Bermond–Vorst Alexithymia Questionnaire (BVAQ), and mentalizing with the Theory of Mind (ToM) test. The Symptom Checklist-90 Revised (SCL-90-R) and the Scale for Interpersonal Behaviour (SIB) were used to record aspects of psychological well-being and social interaction.ResultsPatients showed higher levels of cognitive alexithymia than controls. They also experienced more social distress, but the frequency of engaging in social situations did not differ. Facial emotion recognition was only slightly impaired.ConclusionsHigher levels of alexithymia and social discomfort are part of the behavioural phenotype of NS. However, patients with NS have relatively intact perception of emotions in others and unimpaired mentalizing. These results provide insight into the underlying mechanisms of social daily life functioning in this patient group.

Impaired Recognition of Negative Facial Emotions in Body Dysmorphic Disorder

2019 ◽  
Vol 25 (08) ◽  
pp. 884-889 ◽  
Author(s):  
Sally A. Grace ◽  
Wei Lin Toh ◽  
Ben Buchanan ◽  
David J. Castle ◽  
Susan L. Rossell
Keyword(s):  
Emotion Recognition ◽  
Face Processing ◽  
Body Dysmorphic Disorder ◽  
Recognition Task ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Emotional Expressions ◽  
Healthy Controls ◽  
Facial Emotions ◽  
Healthy Control

Abstract Objectives: Patients with body dysmorphic disorder (BDD) have difficulty in recognising facial emotions, and there is evidence to suggest that there is a specific deficit in identifying negative facial emotions, such as sadness and anger. Methods: This study investigated facial emotion recognition in 19 individuals with BDD compared with 21 healthy control participants who completed a facial emotion recognition task, in which they were asked to identify emotional expressions portrayed in neutral, happy, sad, fearful, or angry faces. Results: Compared to the healthy control participants, the BDD patients were generally less accurate in identifying all facial emotions but showed specific deficits for negative emotions. The BDD group made significantly more errors when identifying neutral, angry, and sad faces than healthy controls; and were significantly slower at identifying neutral, angry, and happy faces. Conclusions: These findings add to previous face-processing literature in BDD, suggesting deficits in identifying negative facial emotions. There are treatment implications as future interventions would do well to target such deficits.

scholarly journals Do You See What I See -- Exploring the Role of Personality in Emotion Recognition using a Priming Paradigm

2020 ◽  
Author(s):  
Parama Gupta ◽  
Deepshikha Ray ◽  
Sukanto Sarkar
Keyword(s):  
Young Adult ◽  
Emotion Recognition ◽  
Recognition Task ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Mediating Role ◽  
Priming Paradigm ◽  
Healthy Participants

The current study explored the mediating role of Neuroticism and Psychoticism involving young adult healthy participants who performed a facial emotion recognition task.

scholarly journals Facial Sadness Recognition is Modulated by Estrogen Receptor Gene Polymorphisms in Healthy Females

2018 ◽  
Vol 8 (12) ◽  
pp. 219 ◽  
Author(s):  
Mayra Gutiérrez-Muñoz ◽  
Martha Fajardo-Araujo ◽  
Erika González-Pérez ◽  
Victor Aguirre-Arzola ◽  
Silvia Solís-Ortiz
Keyword(s):  
Estrogen Receptor ◽  
Response Time ◽  
Emotion Recognition ◽  
Facial Expressions ◽  
Emotional Processing ◽  
Receptor Gene ◽  
Recognition Task ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
The Impact

Polymorphisms of the estrogen receptor ESR1 and ESR2 genes have been linked with cognitive deficits and affective disorders. The effects of these genetic variants on emotional processing in females with low estrogen levels are not well known. The aim was to explore the impact of the ESR1 and ESR2 genes on the responses to the facial emotion recognition task in females. Postmenopausal healthy female volunteers were genotyped for the polymorphisms Xbal and PvuII of ESR1 and the polymorphism rs1256030 of ESR2. The effect of these polymorphisms on the response to the facial emotion recognition of the emotions happiness, sadness, disgust, anger, surprise, and fear was analyzed. Females carrying the P allele of the PvuII polymorphism or the X allele of the Xbal polymorphism of ESR1 easily recognized facial expressions of sadness that were more difficult for the women carrying the p allele or the x allele. They displayed higher accuracy, fast response time, more correct responses, and fewer omissions to complete the task, with a large effect size. Women carrying the ESR2 C allele of ESR2 showed a faster response time for recognizing facial expressions of anger. These findings link ESR1 and ESR2 polymorphisms in facial emotion recognition of negative emotions.

Gaze behavior in mixed facial emotion recognition task

2018 ◽  
Vol 131 ◽  
pp. S129
Author(s):  
M. Konstantinova ◽  
K. Shedenko ◽  
L. Boyko ◽  
O. Perepelkina ◽  
E. Kazimirova ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Recognition Task ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Gaze Behavior

scholarly journals Facial emotion recognition in adolescents with psychotic-like experiences: a school-based sample from the general population

2012 ◽  
Vol 42 (10) ◽  
pp. 2157-2166 ◽  
Author(s):  
S. Roddy ◽  
L. Tiedt ◽  
I. Kelleher ◽  
M. C. Clarke ◽  
J. Murphy ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Facial Emotion Recognition ◽  
Self Report ◽  
Facial Emotion ◽  
Psychotic Symptoms ◽  
Cross Sectional ◽  
School Based ◽  
Schizophrenia Spectrum ◽  
Increased Risk ◽  
The Relationship

BackgroundPsychotic symptoms, also termed psychotic-like experiences (PLEs) in the absence of psychotic disorder, are common in adolescents and are associated with increased risk of schizophrenia-spectrum illness in adulthood. At the same time, schizophrenia is associated with deficits in social cognition, with deficits particularly documented in facial emotion recognition (FER). However, little is known about the relationship between PLEs and FER abilities, with only one previous prospective study examining the association between these abilities in childhood and reported PLEs in adolescence. The current study was a cross-sectional investigation of the association between PLEs and FER in a sample of Irish adolescents.MethodThe Adolescent Psychotic-Like Symptom Screener (APSS), a self-report measure of PLEs, and the Penn Emotion Recognition-40 Test (Penn ER-40), a measure of facial emotion recognition, were completed by 793 children aged 10–13 years.ResultsChildren who reported PLEs performed significantly more poorly on FER (β=−0.03, p=0.035). Recognition of sad faces was the major driver of effects, with children performing particularly poorly when identifying this expression (β=−0.08, p=0.032).ConclusionsThe current findings show that PLEs are associated with poorer FER. Further work is needed to elucidate causal relationships with implications for the design of future interventions for those at risk of developing psychosis.

scholarly journals Facial Emotion Recognition Impairment in Patients with Parkinson's Disease and Isolated Apathy

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Mercè Martínez-Corral ◽  
Javier Pagonabarraga ◽  
Gisela Llebaria ◽  
Berta Pascual-Sedano ◽  
Carmen García-Sánchez ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Emotion Recognition ◽  
Emotional Processing ◽  
Recognition Task ◽  
Executive Dysfunction ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Affective Processing ◽  
Affective Disturbances

Apathy is a frequent feature of Parkinson's disease (PD), usually related with executive dysfunction. However, in a subgroup of PD patients apathy may represent the only or predominant neuropsychiatric feature. To understand the mechanisms underlying apathy in PD, we investigated emotional processing in PD patients with and without apathy and in healthy controls (HC), assessed by a facial emotion recognition task (FERT). We excluded PD patients with cognitive impairment, depression, other affective disturbances and previous surgery for PD. PD patients with apathy scored significantly worse in the FERT, performing worse in fear, anger, and sadness recognition. No differences, however, were found between nonapathetic PD patients and HC. These findings suggest the existence of a disruption of emotional-affective processing in cognitive preserved PD patients with apathy. To identify specific dysfunction of limbic structures in PD, patients with isolated apathy may have therapeutic and prognostic implications.

Facial emotion recognition in schizotypy: The role of accuracy and social cognitive bias

2010 ◽  
Vol 16 (3) ◽  
pp. 474-483 ◽  
Author(s):  
LAURA A. BROWN ◽  
ALEX S. COHEN
Keyword(s):  
Quality Of Life ◽  
Emotion Recognition ◽  
Social Cognitive ◽  
Rating Scale ◽  
Life Quality ◽  
Recognition Task ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Schizotypal Personality

AbstractFacial emotion recognition deficits have been widely investigated in individuals with schizophrenia; however, it remains unclear whether these deficits reflect a trait-like vulnerability to schizophrenia pathology present in individuals at risk for the disorder. Although some studies have investigated emotion recognition in this population, findings have been mixed. The current study uses a well-validated emotion recognition task, a relatively large sample, and examines the relationship between emotion recognition, symptoms, and overall life quality. Eighty-nine individuals with psychometrically defined schizotypy and 27 controls completed the Schizotypal Personality Questionnaire, Penn Emotion Recognition Test, and a brief version of Lehman’s Quality of Life Interview. In addition to labeling facial emotions, participants rated the valence of faces using a Likert rating scale. Individuals with schizotypy were significantly less accurate than controls when labeling emotional faces, particularly neutral faces. Within the schizotypy sample, both disorganization symptoms and lower quality of life were associated with a bias toward perceiving facial expressions as more negative. Our results support previous research suggesting that poor emotion recognition is associated with vulnerability to psychosis. Although emotion recognition appears unrelated to symptoms, it probably operates by means of different processes in those with particular types of symptoms. (JINS, 2010, 16, 474–483.)

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