A Review on Detection of Autism Spectrum Disorder Using Signal Processing

Abstract

Abstract

Autism is a neural developmental disability associated with impairments in communication and social interaction; it can be detected by various methods such as Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG). MRI is a technique which captures the image of various sections of brain. It is categorised as structural MRI (sMRI) and functional MRI (fMRI). The detection involves capturing the image, removing the unwanted regions of brain, segmenting the images and then it acts as an input for classifier. Another way of diagnosis is by using capturing electroencephalograph (EEG) signal of brain. It captures small brain signals during a particular neural activity. These are captured using electrodes and then preprocessed to extract features. These extracted features are the inputs for classifier. This is a review paper that talks about autism and discusses various computer aided techniques based on the concepts of signal processing which are used for its diagnosis.

Keywords: Autism Spectrum Disorder, EEG, MRI, face processing, classifier

Cite this Article

Tulikapriya Sinha, Mousami V. Munot, Sreemathy R. A Review on Detection of Autism Spectrum Disorder Using Signal Processing. Current Trends in Signal Processing. 2018; 8(2): 12–24p.