Literature DB >> 29432106

A Feasibility Study of Autism Behavioral Markers in Spontaneous Facial, Visual, and Hand Movement Response Data.

Manar D Samad, Norou Diawara, Jonna L Bobzien, John W Harrington, Megan A Witherow, Khan M Iftekharuddin.   

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disability with atypical traits in behavioral and physiological responses. These atypical traits in individuals with ASD may be too subtle and subjective to measure visually using tedious methods of scoring. Alternatively, the use of intrusive sensors in the measurement of psychophysical responses in individuals with ASD may likely cause inhibition and bias. This paper proposes a novel experimental protocol for non-intrusive sensing and analysis of facial expression, visual scanning, and eye-hand coordination to investigate behavioral markers for ASD. An institutional review board approved pilot study is conducted to collect the response data from two groups of subjects (ASD and control) while they engage in the tasks of visualization, recognition, and manipulation. For the first time in the ASD literature, the facial action coding system is used to classify spontaneous facial responses. Statistical analyses reveal significantly (p <0.01) higher prevalence of smile expression for the group with ASD with the eye-gaze significantly averted (p<0.05) from viewing the face in the visual stimuli. This uncontrolled manifestation of smile without proper visual engagement suggests impairment in reciprocal social communication, e.g., social smile. The group with ASD also reveals poor correlation in eye-gaze and hand movement data suggesting deficits in motor coordination while performing a dynamic manipulation task. The simultaneous sensing and analysis of multimodal response data may provide useful quantitative insights into ASD to facilitate early detection of symptoms for effective intervention planning.

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Year:  2018        PMID: 29432106     DOI: 10.1109/TNSRE.2017.2768482

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  5 in total

1.  Assessing Social Communication and Collaboration in Autism Spectrum Disorder Using Intelligent Collaborative Virtual Environments.

Authors:  Lian Zhang; Amy S Weitlauf; Ashwaq Zaini Amat; Amy Swanson; Zachary E Warren; Nilanjan Sarkar
Journal:  J Autism Dev Disord       Date:  2020-01

Review 2.  Sensor-Based Technology for Social Information Processing in Autism: A Review.

Authors:  Andrea E Kowallik; Stefan R Schweinberger
Journal:  Sensors (Basel)       Date:  2019-11-04       Impact factor: 3.576

3.  Application of Machine Learning Techniques to Detect the Children with Autism Spectrum Disorder.

Authors:  Mengyi Liao; Hengyao Duan; Guangshuai Wang
Journal:  J Healthc Eng       Date:  2022-03-25       Impact factor: 2.682

4.  Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism.

Authors:  Kimberly L H Carpenter; Jordan Hahemi; Kathleen Campbell; Steven J Lippmann; Jeffrey P Baker; Helen L Egger; Steven Espinosa; Saritha Vermeer; Guillermo Sapiro; Geraldine Dawson
Journal:  Autism Res       Date:  2020-09-14       Impact factor: 5.216

5.  Computational Assessment of Facial Expression Production in ASD Children.

Authors:  Marco Leo; Pierluigi Carcagnì; Cosimo Distante; Paolo Spagnolo; Pier Luigi Mazzeo; Anna Chiara Rosato; Serena Petrocchi; Chiara Pellegrino; Annalisa Levante; Filomena De Lumè; Flavia Lecciso
Journal:  Sensors (Basel)       Date:  2018-11-16       Impact factor: 3.576

  5 in total

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