Estimation of Adverse Drug Effect in Autism Children through Repetitive behavior Analysis from Thermal Video Processing and Machine Learning Algorithms

Abstract

In this review paper, the adverse drug effect in autism children is studied after consuming the prescribed drug dosage level suggested by Physicians through computer vision-based physiological monitoring. The prescription of drug and dosage level for the autism children is done after clinical signs such as repetitive behaviour, dyspraxia, abnormal gait, and abnormality of motor functions for accurate prescription of drug dosage level. Autism children need more effective and continuous monitoring for assessment and measurement of clinical signs. The continuous and effective monitoring of autism children for the clinical sign is a challenging task for any physician. In this paper, the above problem-solve through the Drug Based Autism Child Repetitive Behaviour Estimation (DARBE) method, which is continuous monitoring of the autistic child by a thermal imaging system. Thermal imaging captures the autistic child repetitive behaviour analysis, spatial temperature levels are recorded for measurements such as Mood assessment, heart rate, and variability, finger temperature, and the temperature of the skin. The thermal imaging and logistic regression predicts the clinical signs of autistic children through thermal video processing for accurate dosage level perception and avoids adverse drug effects because of over/under dosage level of drugs.