scholarly journals Reduced emotion recognition from nonverbal cues in anorexia nervosa

2021 ◽  
Author(s):  
Maximilian Blomberg ◽  
Katja Schlegel ◽  
Linda Stoll ◽  
Hagen Febry ◽  
Wally Wünsch‐Leiteritz ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Emotion Recognition ◽  
Nonverbal Cues

Emotion regulation, emotion recognition, and empathy in adolescents with anorexia nervosa

2019 ◽  
Vol 24 (5) ◽  
pp. 825-834 ◽  
Author(s):  
Kevser Nalbant ◽  
Bilge Merve Kalaycı ◽  
Devrim Akdemir ◽  
Sinem Akgül ◽  
Nuray Kanbur
Keyword(s):  
Emotion Regulation ◽  
Anorexia Nervosa ◽  
Emotion Recognition

Emotion recognition and regulation in anorexia nervosa

2009 ◽  
Vol 16 (4) ◽  
pp. 348-356 ◽  
Author(s):  
Amy Harrison ◽  
Sarah Sullivan ◽  
Kate Tchanturia ◽  
Janet Treasure
Keyword(s):  
Anorexia Nervosa ◽  
Emotion Recognition

Emotion Recognition in Blended Facial Expressions in Women with Anorexia Nervosa

2015 ◽  
Vol 24 (1) ◽  
pp. 34-42 ◽  
Author(s):  
Marcela Marin Dapelo ◽  
Simon Surguladze ◽  
Robin Morris ◽  
Kate Tchanturia
Keyword(s):  
Anorexia Nervosa ◽  
Emotion Recognition ◽  
Facial Expressions

scholarly journals Exploring Emotion Recognition in Adults and Adolescents with Anorexia Nervosa Using a Body Motion Paradigm

2015 ◽  
Vol 23 (4) ◽  
pp. 262-268 ◽  
Author(s):  
Katie Lang ◽  
Marcela Marin Dapelo ◽  
Mizanur Khondoker ◽  
Robin Morris ◽  
Simon Surguladze ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Emotion Recognition ◽  
Body Motion

scholarly journals Visual scanning during emotion recognition in long-term recovered anorexia nervosa: An eye-tracking study

2019 ◽  
Vol 52 (6) ◽  
pp. 691-700 ◽  
Author(s):  
Lisa Dinkler ◽  
Sandra Rydberg Dobrescu ◽  
Maria Råstam ◽  
I. Carina Gillberg ◽  
Christopher Gillberg ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Eye Tracking ◽  
Emotion Recognition ◽  
Visual Scanning

scholarly journals Improving emotion recognition in anorexia nervosa: An experimental proof‐of‐concept study

2020 ◽  
Vol 53 (6) ◽  
pp. 945-953 ◽  
Author(s):  
Mira A. Preis ◽  
Katja Schlegel ◽  
Linda Stoll ◽  
Maximilian Blomberg ◽  
Hagen Schmidt ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Emotion Recognition ◽  
Proof Of Concept ◽  
Experimental Proof ◽  
Concept Study

scholarly journals Emotions in Virtual Reality

2021 ◽  
Author(s):  
Darlene Barker ◽  
Haim Levkowitz
Keyword(s):  
Machine Learning ◽  
Virtual Reality ◽  
Emotion Recognition ◽  
Nonverbal Cues ◽  
Haptic Devices ◽  
The One

One of the first senses we learn about at birth is touch, and the one sense that can deepen our experience of many situations is touch. In this paper we propose the use of emotions including touch within virtual reality (VR) to create a simulated closeness that currently can only be achieved with in-person interactions and communications. With the simulation of nonverbal cues, we can enhance a conversation or interaction in VR. Using haptic devices to deliver the simulation of touch between users via sensors and machine learning for emotion recognition based on data collected; all working towards simulated closeness in communication despite distance or being in VR. We present a direction for further research on how to simulate inperson communication within VR with the use of emotion recognition and touch to achieve a close-to-real interaction.

scholarly journals Emotion Recognition Abilities in Adults with Anorexia Nervosa are Associated with Autistic Traits

2020 ◽  
Vol 9 (4) ◽  
pp. 1057 ◽  
Author(s):  
Jess Kerr-Gaffney ◽  
Luke Mason ◽  
Emily Jones ◽  
Hannah Hayward ◽  
Jumana Ahmad ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Emotion Recognition ◽  
Recognition Performance ◽  
Treatment Strategies ◽  
Autistic Traits ◽  
Autism Diagnostic Observation Schedule ◽  
Autism Spectrum ◽  
Self Report ◽  
Future Research ◽  
Comorbid Psychopathology

Difficulties in socio-emotional functioning are proposed to contribute to the development and maintenance of anorexia nervosa (AN). This study aimed to examine emotion recognition abilities in individuals in the acute and recovered stages of AN compared to healthy controls (HCs). A second aim was to examine whether attention to faces and comorbid psychopathology predicted emotion recognition abilities. The films expressions task was administered to 148 participants (46 AN, 51 recovered AN, 51 HC) to assess emotion recognition, during which attention to faces was recorded using eye-tracking. Comorbid psychopathology was assessed using self-report questionnaires and the Autism Diagnostic Observation Schedule–2nd edition (ADOS-2). No significant differences in emotion recognition abilities or attention to faces were found between groups. However, individuals with a lifetime history of AN who scored above the clinical cut-off on the ADOS-2 displayed poorer emotion recognition performance than those scoring below cut-off and HCs. ADOS-2 scores significantly predicted emotion recognition abilities while controlling for group membership and intelligence. Difficulties in emotion recognition appear to be associated with high autism spectrum disorder (ASD) traits, rather than a feature of AN. Whether individuals with AN and high ASD traits may require different treatment strategies or adaptations is a question for future research.

Deficits of Emotion Recognition in Female College Students with Anorexia Nervosa Trait

2020 ◽  
Vol 27 (12) ◽  
pp. 1-26
Author(s):  
Young-Sun Park ◽  
Myung-Sun Kim
Keyword(s):  
College Students ◽  
Anorexia Nervosa ◽  
Emotion Recognition ◽  
Female College Students ◽  
Female College

scholarly journals Automated Recognition of Emotion Appraisals

2015 ◽  
pp. 338-351 ◽  
Author(s):  
Marcello Mortillaro ◽  
Ben Meuleman ◽  
Klaus R. Scherer
Keyword(s):  
Emotion Recognition ◽  
Contextual Information ◽  
Automatic Recognition ◽  
Nonverbal Cues ◽  
Second Step ◽  
Inference Algorithm ◽  
Vocal Expression ◽  
Automated Recognition ◽  
Discrete Emotion ◽  
Emotion Label

Most computer models for the automatic recognition of emotion from nonverbal signals (e.g., facial or vocal expression) have adopted a discrete emotion perspective, i.e., they output a categorical emotion from a limited pool of candidate labels. The discrete perspective suffers from practical and theoretical drawbacks that limit the generalizability of such systems. The authors of this chapter propose instead to adopt an appraisal perspective in modeling emotion recognition, i.e., to infer the subjective cognitive evaluations that underlie both the nonverbal cues and the overall emotion states. In a first step, expressive features would be used to infer appraisals; in a second step, the inferred appraisals would be used to predict an emotion label. The first step is practically unexplored in emotion literature. Such a system would allow to (a) link models of emotion recognition and production, (b) add contextual information to the inference algorithm, and (c) allow detection of subtle emotion states.

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