Emotion recognition in autism spectrum disorder (original) (raw)
Related papers
Recognition of Emotions in Autism
Determining the integrity of emotion recognition in autistic spectrum disorder is important to our theoretical understanding of autism and to teaching social skills. Previous studies have reported both positive and negative results. Here, we take a formal meta-analytic approach, bringing together data from 48 papers testing over 980 participants with autism. Results show there is an emotion recognition difficulty in autism, with a mean effect size of 0.80 which reduces to 0.41 when a correction for publication bias is applied. Recognition of happiness was only marginally impaired in autism, but recognition of fear was marginally worse than recognition of happiness. This meta-analysis provides an opportunity to survey the state of emotion recognition research in autism and to outline potential future directions.
Recognition of Emotions for People with Autism: An Approach to Improve Skills
International Journal of Computer Games Technology
Autism spectrum disorder refers to a neurodevelopmental disorders characterized by repetitive behavior patterns, impaired social interaction, and impaired verbal and nonverbal communication. The ability to recognize mental states from facial expressions plays an important role in both social interaction and interpersonal communication. Thus, in recent years, several proposals have been presented, aiming to contribute to the improvement of emotional skills in order to improve social interaction. In this paper, a game is presented to support the development of emotional skills in people with autism spectrum disorder. The software used helps to develop the ability to recognize and express six basic emotions: joy, sadness, anger, disgust, surprise, and fear. Based on the theory of facial action coding systems and digital image processing techniques, it is possible to detect facial expressions and classify them into one of the six basic emotions. Experiments were performed using four pub...
Lecture Notes in Computer Science, 2009
This paper describes the design and development of both software to create social interaction modules on a virtual reality (VR) platform and individualized affective models for affect recognition of children with autism spectrum disorders (ASD), which includes developing tasks for affect elicitation and using machine-learning mathematical tools for reliable affect recognition. A VR system will be formulated that can present realistic social communication tasks to the children with ASD and can monitor their affective response using physiological signals, such as cardiovascular activities including electrocardiogram, impedance cardiogram, photoplethysmogram, and phonocardiogram; electrodermal activities including tonic and phasic responses from galvanic skin response; electromyogram activities from corrugator supercilii, zygomaticus major, and upper trapezius muscles; and peripheral temperature. This affect-sensitive system will be capable of systematically manipulating aspects of social communication to more fully understand its salient components for children with ASD.
Children in Autism Spectrum Disorder (ASD) are characterized by impairments in social skills and they usually face difficulties in recognizing facial emotion expressions. Early intervention and treatment is of major concern and therefore a number of detection and teaching methods have been developed, including the use of ICT. This article presents a brief but extensive literature review on the way tutors are represented in digital environments. The results showed that there is a need for further investigation on the effectiveness of the methods used for the interaction of children on ASD with technology tools, as well as on knowledge transfer. Since there is a lack of empirical data concerning the preference of different interaction modalities by children with ASD, this article also reports on an exploratory study conducted to investigate the acceptance and preference of three different real-time modalities used in facial emotion recognition by two children with ASD (low and high functioning autism). The results indicated a discrepancy between the two children which can be mainly attributed to the differences accompanied the categorization of children with ASD in low and high functioning autism.
Responses to Nonverbal Behaviour of Dynamic Virtual Characters in High-Functioning Autism
Journal of Autism and Developmental Disorders, 2010
We investigated feelings of involvement evoked by nonverbal behaviour of dynamic virtual characters in 20 adults with high-functioning autism (HFA) and high IQ as well as 20 IQ-matched control subjects. The effects of diagnostic group showed that subjects with autism experienced less ''contact'' and ''urge'' to establish contact across conditions and less ''interest'' than controls in a condition with meaningful facial expressions. Moreover, the analyses within groups revealed that nonverbal behaviour had less influence on feelings in HFA subjects. In conclusion, disturbances of HFA subjects in experiencing involvement in social encounters with virtual characters displaying nonverbal behaviour do not extend to all kinds of feelings, suggesting different pathways in the ascription of involvement in social situations.
Emotion recognition in autism: Verbal and nonverbal information
Development and Psychopathology, 1997
This study examined the roles of verbal and nonverbal sources of information in the ability of persons with and without autism to recognize emotion. Child, adolescent, and young adult participants in four groups [Lower Functioning Autism (LFA) (n = 17), High Functioning Autism (HFA) (n = 18), Lower Functioning Comparison (LFC) (n = 18), and High Functioning Comparison (HFC) (n = 23)] identified emotions shown (happy, angry, sad, surprised, or neutral) in video clips of individuals expressing emotion verbally, nonverbally, or both. Verbal expressions of emotion were either Explicit, Implicit, or Neutral, whereas nonverbal expressions were Animate or Flat (3 × 2). Pairwise ANCOVAs indicated no group differences between HFA and HFC groups or between the LFA and LFC groups, and indicated instead group differences between higher and lower functioning persons. With groups collapsed into High Functioning (HF) and Lower Functioning (LF), significant group differences were found. Performance...
Journal of Autism and Developmental Disorders, 2014
A new virtual reality task was employed which uses preference for interpersonal distance to social stimuli to examine social motivation and emotion perception in children with Autism Spectrum Disorders. Nineteen high function children with higher functioning Autism Spectrum Disorder (HFASD) and 23 age, gender, and IQ matched children with typical development (TD) used a joy stick to position themselves closer or further from virtual avatars while attempting to identify six emotions expressed by the avatars, happiness, fear, anger, disgust, sadness, and surprise that were expressed at different levels of intensity. The results indicated that children with HFASD displayed significantly less approach behavior to the positive happy expression than did children with TD,
psychological reports
People who have a high degree of autistic traits often underperform on theory of mind tasks such as perspective-taking or facial emotion recognition compared to those with lower levels of autistic traits. However, some research suggests that this may not be the case if the agent they are evaluating is anthropomorphic (i.e. animal or cartoon) rather than typically human. The present studies examined the relation between facial emotion recognition and autistic trait profiles in over 750 adults using either a standard or cartoon version of the Reading the Mind in the Eyes (RME) test. Results showed that those scoring above the clinical cut off for autistic traits on the Autism Quotient performed significantly worse than those with the lowest levels of autistic traits on the standard RME, while scores across these groups did not differ substantially on the cartoon version of the task. These findings add further evidence that theory of mind ability such as facial emotion recognition is not at a global deficit in those with a high degree of autistic traits. Instead, differences in this ability may be specific to evaluating human agents.