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Autism Spectrum Disorder (ASD) is a developmental disorder that often impairsa child's normal development of the brain. According to CDC, it is estimatedthat 1 in 6 children in the US suffer from development disorders, and 1 in 68children in the US suffer from ASD. This condition has a negative impact on aperson's ability to hear, socialize and communicate. Overall, ASD has a broadrange of symptoms and severity; hence the term spectrum is used. One of themain contributors to ASD is known to be genetics. Up to date, no suitable curefor ASD has been found. Early diagnosis is crucial for the long-term treatmentof ASD, but this is challenging due to the lack of a proper objective measures.Subjective measures often take more time, resources, and have false positivesor false negatives. There is a need for efficient objective measures that canhelp in diagnosing this disease early as possible with less effort.  EEG measures the electric signals of the brain via electrodes placed onvarious places on the scalp. These signals can be used to study complexneuropsychiatric issues. Studies have shown that EEG has the potential to beused as a biomarker for various neurological conditions including ASD. Thischapter will outline the usage of EEG measurement for the classification of ASDusing machine learning algorithms.

Electroencephalogram (EEG) for Delineating Objective Measure of Autism Spectrum Disorder (ASD) (Extended Version)