New Technologies as Promising Tools for Assessing Facial Emotion Expressions Impairments in ASD: A Systematic Review

新技术作为评估自闭症谱系障碍患者面部表情障碍的有效工具:系统性综述

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Abstract

The ability to recognize and express emotions from facial expressions are essential for successful social interactions. Facial Emotion Recognition (FER) and Facial Emotion Expressions (FEEs), both of which seem to be impaired in Autism Spectrum Disorders (ASD) and contribute to socio-communicative difficulties, participate in the diagnostic criteria for ASD. Only a few studies have focused on FEEs processing and the rare behavioral studies of FEEs in ASD have yielded mixed results. Here, we review studies comparing the production of FEEs between participants with ASD and non-ASD control subjects, with a particular focus on the use of automatic facial expression analysis software. A systematic literature search in accordance with the PRISMA statement identified 20 reports published up to August 2020 concerning the use of new technologies to evaluate both spontaneous and voluntary FEEs in participants with ASD. Overall, the results highlight the importance of considering socio-demographic factors and psychiatric co-morbidities which may explain the previous inconsistent findings, particularly regarding quantitative data on spontaneous facial expressions. There is also reported evidence for an inadequacy of FEEs in individuals with ASD in relation to expected emotion, with a lower quality and coordination of facial muscular movements. Spatial and kinematic approaches to characterizing the synchrony, symmetry and complexity of facial muscle movements thus offer clues to identifying and exploring promising new diagnostic targets. These findings have allowed hypothesizing that there may be mismatches between mental representations and the production of FEEs themselves in ASD. Such considerations are in line with the Facial Feedback Hypothesis deficit in ASD as part of the Broken Mirror Theory, with the results suggesting impairments of neural sensory-motor systems involved in processing emotional information and ensuring embodied representations of emotions, which are the basis of human empathy. In conclusion, new technologies are promising tools for evaluating the production of FEEs in individuals with ASD, and controlled studies involving larger samples of patients and where possible confounding factors are considered, should be conducted in order to better understand and counter the difficulties in global emotional processing in ASD.

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