Automated Delimitation and Classification of Autistic Disorder Using EEG Signal

Abstract

Autism Spectrum Disorder (ASD) is a disturbing neuro-developmental disorder affecting the behavioural ability and communication skills of an individual. Early detection of such prevalent abnormality through EEG pattern analysis with the help of computer-aided diagnostic tools; provide significant relief to the health care professionals for better management and treatment of such patients. This work has been proposed as an investigation of the sensory responsiveness of the children affected by ASD. This ASD is analyzed by extracting the non-linear features of the EEG signal. A total of 73 EEG signals are collected from different patients out of which 41 are affected with ASD and 32 with normal neural activity. These signals are then pre-processed and filtered using a low pass filter and then separated using Independent Component Analysis (ICA) into additive subcomponents. Significant features are extracted, which can be further investigated to identify event-related potential and Non-biological Artifacts. These features are then classified using Support Vector Machine (SVM) with an accuracy of 90.41%. As a result, appropriate sensory profiles can be obtained that may help proper diagnosis and treatment at an early stage.

Keywords:

• EEG
• ASD
• ICA
• SVM
• Brain wave
• Autism

ACKNOWLEDGEMENT

We express our sincere gratitude to the officals of IMS & SUM Hospital, for providing the EEG signals of ASD patients.

Additional information

Notes on contributors

Asit Kumar Subudhi

Asit Subudhi received BE in electronics & communication, in 2005 and MTech in communication system engineering from BPUT, Bhubaneswar, in 2010 and PhD in electronic engineering at SOA deemed to be University in 2018. Presently, working as associate professor in the Department of Electronics & Communication Engineering, SOA University, Odisha, India. He has over 15 years of experience in teaching and his research expertise focuses on biomedical signal and image processing and VLSI design. He is a member of IEEE. Email: [email protected]

Monalisa Mohanty

Monalisa Mohanty received MTech in communication system engineering from BPUT, Bhubaneswar, in 2010 and PhD in electronic engineering at SOA University in 2019. Currently, working as an associate professor in the Department of Electronics and Communication Engineering, at ITER in SOA deemed to be University. She possesses 12 years of experience. Her area of interest is research work in biomedical signal and image processing. She published papers in many reputed journals and conferences. Email: [email protected]

Santanu Kumar Sahoo

Santanu Kumar Sahoo is presently working as associate professor in the Department of ECE, FET, ITER, Siksha ‘O’ Anusandhan deemed to be University, Bhubaneswar, India. He graduated from Utkal University and did his post-graduation at SOA University. He was awarded PhD from SOA University, Bhubaneswar, India. He is a member of the IEEE, IET, and OITS professional societies. He has number of papers in International journals and conferences. His area of research interests includes –biomedical signal and image processing. Email: [email protected]

Saumendra Kumar Mohanty

Saumendra Kumar Mohanty is presently working as associate professor in the Department of ECE, FET, ITER, Siksha ‘O’ Anusandhan deemed to be University, Bhubaneswar, India. He graduated from Utkal University and did his post-graduation at SOA University. He was awarded PhD from VSSUT, Burla, India. He is a member of the IEEE, IET, and OITS professional societies. His area of research interests includes –Wireless communication, antenna engineering, satellite and fiber optic communication. Email: [email protected]

Bibhuprasad Mohanty

Bibhuprasad Mohanty is presently working as professor and head in the Department of ECE, FET, ITER, Siksha ‘O’ Anusandhan deemed to be university, Bhubaneswar, India. He was awarded PhD from IIT, Kharagpur, India. He is a member of the IEEE, IET. He has number of papers in international journals and conferences. His area of research interests includes –signal and image processing in biomedical aplications.