Phase Space Reconstruction of EEG Signals for Classification of ADHD and Control Adults. (March 2020)

• Record Type: Journal Article
• Authors: Kaur, Simranjit; Singh, Sukhwinder; Arun, Priti; Kaur, Damanjeet; Bajaj, Manoj
• Is Part Of: Clinical EEG and neuroscience. Volume 51:Number 2(2020)
• Page Start: 102
• Page End: 113
• Publication Date: 2020-03
• Subjects: attention deficit hyperactivity disorder -- adults -- continuous performance test -- EEG -- phase space reconstruction; Electroencephalography -- Periodicals; Neurosciences -- Periodicals; 616.8047547
• DOI: 10.1177/1550059419876525
• Languages: English
• ISSNs: 1550-0594

Abstract

Attention deficit hyperactivity disorder (ADHD) is a childhood behavioral disorder that can persist into adulthood. Electroencephalography (EEG) plays a significant role in assessing the neurophysiology of ADHD because of its ability to reveal complex brain activity. The present study proposes an EEG-based diagnosis system using the phase space reconstruction technique to classify ADHD and control adults. Electric activity is recorded for 47 ADHD and 50 control adults during the eyes-open, eyes-closed, and Continuous Performance Test (CPT) condition. Various statistical features are extracted from Euclidean distances based on phase space reconstruction of signals. The proposed system is evaluated with 2 feature selection methods (correlation-based feature selection and particle swarm optimization) and 5 machine learning methods (neural dynamic classifier, support vector machine, enhanced probabilistic neural network, k-nearest neighbor, and naive-Bayes classifier). Experimental results showed the highest testing accuracy of 93.3% under the eyes-open, 90% under the eyes-closed, and 100% under the CPT condition. This study focused on the utility of phase space reconstruction of brain signals to discriminate between ADHD and control adults.