Development of a real-time algorithm for the detection of physiological arousal in the presence of motion among children with autism

Anxiety is a clinical concern among some children with autism, for whom such an emotional onset may exacerbate core symptoms. Current treatment options are challenged as many of these children are unaware of their emotional state, and due to autism some children also have difficulties with language and communication which further complicates anxiety diagnoses. In this thesis, we proposed a novel automated anxiety detection algorithm capable of interpreting heart rate arousal in the presence of physical movements , and intuitively notifying the user to engage in anxiety management techniques. The novelty of our proposed algorithm is based on its ability to detect anxiety in presence of motion; this is a challenge as motion and anxiety influence the heart rate similarly. This algorithm was able to account for the changes in heart rate due to motion and detection anxiety with an accuracy, specificity and sensitivity of 92.7% in children with autism.M.H.Sc