ADHD children identification based on EEG using effective connectivity techniques

Shen, Mingkan and Wen, Peng ORCID: https://orcid.org/0000-0003-0939-9145 and Song, Bo and Li, Yan ORCID: https://orcid.org/0000-0002-4694-4926 (2021) ADHD children identification based on EEG using effective connectivity techniques. In: 10th International Conference on Health Information Science (HIS 2021), 25 Oct - 28 Oct 2021, Melbourne, Australia.


Abstract

This paper presents a novel method to identify the Attention deficit hyperactivity disorder (ADHD) children using electroencephalography (EEG) signals and effective connectivity techniques. In this study, the original EEG data is pre-filtered and divided into Delta, Theta, Alpha and Beta bands. And then, the effective connectivity graphs are constructed by applying independent component analysis, multivariate regression model and phase slope index. The measures of clustering coefficient, nodal efficiency and degree centrality in graph theory are used to extract features from these graphs. Statistical analysis based on the standard error of the mean is employed to evaluate the performance in each frequency band. The results show a decreased average clustering coefficient in Delta band for ADHD subjects. Also, in Delta band, the ADHD subjects have increased nodal efficiency and degree centrality in left forehead and decreased in forehead middle.


Statistics for USQ ePrint 45398
Statistics for this ePrint Item
Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published Version + Front Matter in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Date Deposited: 31 Jan 2022 06:58
Last Modified: 09 Mar 2022 05:16
Uncontrolled Keywords: ADHD; EEG; effective connectivity; multivariate regression model; phase slope index; graph theory
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460299 Artificial intelligence not elsewhere classified
Identification Number or DOI: https://doi.org/10.1007/978-3-030-90885-0_7
URI: http://eprints.usq.edu.au/id/eprint/45398

Actions (login required)

View Item Archive Repository Staff Only