Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are neurodevelopmental conditions which impact on a significant number of children and adults. Currently, the diagnosis of such disorders is done by experts who employ standard questionnaires and look for certain behavioural markers through manual observation. Such methods for their diagnosis are not only subjective, difficult to repeat, and costly but also extremely time consuming. In this work, we present a novel methodology to aid diagnostic predictions about the presence absence of ADHD and ASD by automatic visual analysis of a person's behaviour. To do so, we conduct the questionnaires in a computer-mediated way while recording participants with modern RGBD (Colour+Depth) sensors. In contrast to previous automatic approaches which have focussed only detecting certain behavioural markers, our approach provides a fully automatic end-to-end system for directly predicting ADHD and ASD in adults. Using state of the art facial expression analysis based on Dynamic Deep Learning and 3D analysis of behaviour, we attain classification rates of 96 for Controls vs Condition (ADHD ASD) group and 94 for Comorbid (ADHD+ASD) vs ASD only group. We show that our system is a potentially useful time saving contribution to the diagnostic field of ADHD and ASD.
One of the pioneering works in the field of ASD diagnosis was done by @cite_8 . In this work, the authors developed computer vision based methods to identify certain behavioural markers based on Autism Observation Scale for Infants (AOSI) related to visual attention and motor patterns. For assessing visual attention, they focused on 3 main behavioural markers, namely sharing interest, visual tracking and disengagement of attention. These behavioural markers were detected by estimating the head pose in the left-right direction (yaw) and in the up-down direction (pitch). The head pose was estimated by tracking the position of certain facial features (eyes, nose, ear, etc.).
@cite_8
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Attention deficit hypo-activity disorder (ADHD) comprises a deficit in behavioral inhibition. A theoretical model is constructed that links inhibition to 4 executive neuropsychological functions that appear to depend on it for their effective execution: (a) working memory, (b) self-regulation of affect-motivation-arousal, (c) internalization of speech, and (d) reconstitution (behavioral analysis and synthesis). Extended to ADHD, the model predicts that ADHD should be associated with secondary impairments in these 4 executive abilities and the motor control they afford. The author reviews evidence for each of these domains of functioning and finds it to be strongest for deficits in behavioral inhibition, working memory, regulation of motivation, and motor control in those with ADHD. Although the model is promising as a potential theory of self-control and ADHD, far more research is required to evaluate its merits and the many predictions it makes about ADHD.