Automatic detection of stereotyped movements in autistic children using the Kinect sensor Online publication date: Fri, 18-Jan-2019
by Maha Jazouli; Aicha Majda; Djamal Merad; Rachid Aalouane; Arsalane Zarghili
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 29, No. 3, 2019
Abstract: Autism Spectrum Disorders (ASD) is a developmental disorder that affects communications, social skills or behaviours that can occur in some people. Children or adults with ASD often have repetitive motor movements or unusual behaviours. The objective of this work is to automatically detect stereotypical motor movements in real time using Kinect sensor. The approach is based on the $P Point-Cloud Recogniser to identify multi-stroke gestures as point clouds. This paper presents new methodology to automatically detect five stereotypical motor movements: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. With many ASD-children, our proposed system gives us satisfactory results. This can help to implement a smart video surveillance system and then helps clinicians in the diagnosing ASD.
Online publication date: Fri, 18-Jan-2019
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biomedical Engineering and Technology (IJBET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com