Detection of Autism Spectrum Disorder using EEG signals

Project Title

Detection of Autism Spectrum Disorder using EEG signals

Project Area of Specialization Computer ScienceProject Summary

Electroencephalography (EEG) is a measure of voltages caused due to neural activities within the brain. EEG is a recommended tool for diagnosing neurological problems because it is non-invasive and can be recorded over a longer time-period. The children with Autism Spectrum Disorder (ASD) have difficulty in expressing their emotions due to their inability of proper information processing in brain. Our project will use these signals to classify the subject as Autistic or neurotypical.
 

Project Objectives

The objective of this project is to create a software that will diagnose ASD through EEG
signals by using the concepts and techniques of Machine learning.
 

Project Implementation Method

The project uses lightweight convolutional neural network with EEGNet to classify given
raw EEG data as either a)Autistic or b)Non-autistic.

Benefits of the Project

The project can be used in medical centers and hospitals and can be used to help get early diagnosis of patients with ASD.
 

Technical Details of Final Deliverable

Not only will there will be a working software that detects ASD but our project will also use signals from an EEG set and sort them out If they lay on the spectrum or not.

Part one of our project has been completed and it is a working prototype based on lightweight CNN that classifies EEG by EEG_Net into two main groups autistic and, neurotypical.

Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther Industries IT Core Technology OthersOther TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	0
Emotiv's EPOC X	Equipment	0	70000	0