DTWDIR: AN ENHANCED DTW ALGORITHM FOR AUTISTIC CHILD BEHAVIOUR MONITORING

Autism has symptoms can hardly be recognized in the early stages of the disease, and it affects the child's
mental health on the long term. Autism can be identified by parents monitoring to the child and diagnosed
by psychiatrists using an international standard checklist. The checklist questions should be answered by
the parent and psychiatrist to determine the risk level of autism (high, medium, or low risk). It is hard for
parents to monitor more than 20 child's behaviours at the same time regardless lack of accuracy for
answering on most of these questions. We propose a system for monitoring autistic child behaviours by
analysing accelerometer data collected from wearable mobile device. The behaviours are recognized by
using a novel algorithm called DTWDir that based on calculating displacement and direction between two
signals. DTWDir is evaluated by comparing it to KNN, classical Dynamic Time Warping (DTW), and One
Dollar Recognition ($1) algorithms. The results show that DTWDir accuracy is higher than the others.