Department of MCA, Sardar Patel Institute of Technology, Mumbai University, Mumbai, India
Perspective
Predicting Motor Control in Autism by Measuring Brain Activities and Characterising Motor Impairments
Author(s): Zaibunnisa L.H. Malik* and Pooja Raundale
The proportion of children with ASD at risk for a motor impairment was very high at 86.9%. Children with ASD did not outgrow their motor impairments and continued to present with a risk for Developmental Coordination Disorder (DCD) even into adolescence. Yet, only 31.6% of children were receiving physical therapy services. To diagnose ASD, the clinical standardized tests are being used. To test and predict ASD the lengthy diagnostic time is required and also these tests are very costly. Machine learning techniques are being used in place of traditional methods to reduce the time and cost required to predict ASD diagnose. The field of Machine Learning, a branch of Artificial Intelligence, is utilized to diagnose Autism Spectrum Disorder (ASD) by treating it as a classification task. The proposed techniques are evaluated on six different non-clinically ASD datasets. We have applied mode.. View More»
Spanish 
Chinese 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi 