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

作者：Samad Manar D; Diawara Norou; Bobzien Jonna L; Harrington John W; Witherow Megan A; Iftekharuddin Khan M^*

来源：IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2018, 26(2): 353-361.

DOI：10.1109/TNSRE.2017.2768482

• Autism spectrum disorders
• psychophysical study
• behavioral marker
• facial action coding
• multimodal physiological measurement
• eye-tracking
• eye-hand coordination

Autism spectrumdisorder (ASD) is a neurodevelopmental disability with atypical traits in behavioral and physiological responses. These atypical traits in individuals with ASDmay be too subtle and subjective tomeasure visually using tediousmethods 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 visualengagementsuggests impairment in reciprocalsocial 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 datamay provide useful quantitative insights into ASD to facilitate early detection of symptoms for effective intervention planning.

• 出版日期2018-2