Cognitive Behavior: Identification of Autism Disorder in Individuals Based on EEG Signal Using Neural Network Methods
Keywords:
Deep Learning, Autism, Accuracy, Sensitivity, Specificity, PerformanceAbstract
Autism is the word that is used for describing a set of neurodevelopmental disorders. These kinds of disorders have issues with communication and interaction with people. Autism is a Cognitive Disorder it leads to Slow down the Brain Development. Individuals of Autistic find difficulties in learning, talking with others. Autistic people having trouble in learning new things, expressing new thoughts and adapting to new situations, among the others. Because they are unable to interact appropriately with others, they get separated from society. Autistic People are unable to comprehend the actions and intentions of others, and they have trouble understanding from outside their routine. The two commonly used methods are Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder. People with autism usually explain restricted, repetitive and patterns of character. Based on the centers of disease control autism affected level is estimated. Now Deep Learning (DL) models also play an important role in healthcare fields due to their exactness and better outcome. In this research article uses LSTM, CNN, and MLP models are used to identify the autism diseases from the patients EEG (ElectroEncephalogram) signals in an earlier manner. Among these three models, LSTM provides a better result in terms of sensitivity, specificity, and accuracy. These classifiers are implemented using Python programming.
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