Introduction: Monitoring neurophysiological signals and neuroimaging helps the researchers to identify the relations between the major disorders in neurodevelopmental and behavioural changes. Specifically, the brain typical pattern that leads to Autism Spectrum Disorders (ASD) can be analyzed in children with the signals effectively. Objectives: Early identification of Autism Spectrum Disorders syndrome helps the parents to decide about the therapies and treatments required for improving their day to day activities. Materials and Methods: Different analyses performed by various researchers using machine learning algorithms using the EEG and ECG signals have been presented. Different techniques and devices used for acquiring the data through various experiments are also presented. Results: This paper presented a few techniques followed by various researchers; accuracy, sensitivity, recall achieved by the methodologies have been presented. Conclusion: Data collection plays a major role in analyzing the Autism Spectrum Disorders where most of the researches find it very difficult and early diagnosis also plays a major role in the improvement the Autism Spectrum Disorders children.