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      Measuring Engagement in Robot-Assisted Autism Therapy: A Cross-Cultural Study

      , , , ,
      Frontiers in Robotics and AI
      Frontiers Media SA

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          A survey of affect recognition methods: audio, visual, and spontaneous expressions.

          Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions despite the fact that deliberate behaviour differs in visual appearance, audio profile, and timing from spontaneously occurring behaviour. To address this problem, efforts to develop algorithms that can process naturally occurring human affective behaviour have recently emerged. Moreover, an increasing number of efforts are reported toward multimodal fusion for human affect analysis including audiovisual fusion, linguistic and paralinguistic fusion, and multi-cue visual fusion based on facial expressions, head movements, and body gestures. This paper introduces and surveys these recent advances. We first discuss human emotion perception from a psychological perspective. Next we examine available approaches to solving the problem of machine understanding of human affective behavior, and discuss important issues like the collection and availability of training and test data. We finally outline some of the scientific and engineering challenges to advancing human affect sensing technology.
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            Motor coordination in autism spectrum disorders: a synthesis and meta-analysis.

            Are motor coordination deficits an underlying cardinal feature of Autism Spectrum Disorders (ASD)? Database searches identified 83 ASD studies focused on motor coordination, arm movements, gait, or postural stability deficits. Data extraction involved between-group comparisons for ASD and typically developing controls (N = 51). Rigorous meta-analysis techniques including random effects models, forest and funnel plots, I (2), publication bias, fail-safe analysis, and moderator variable analyses determined a significant standardized mean difference effect equal to 1.20 (SE = 0.144; p <0.0001; Z = 10.49). This large effect indicated substantial motor coordination deficits in the ASD groups across a wide range of behaviors. The current overall findings portray motor coordination deficits as pervasive across diagnoses, thus, a cardinal feature of ASD.
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              Is there universal recognition of emotion from facial expression? A review of the cross-cultural studies.

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                Author and article information

                Journal
                Frontiers in Robotics and AI
                Front. Robot. AI
                Frontiers Media SA
                2296-9144
                July 27 2017
                July 27 2017
                : 4
                Article
                10.3389/frobt.2017.00036
                0e6d3bf2-6a02-40d7-9aa7-b16f40b74291
                © 2017
                History

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