Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals
Download
Download
Download
Full text for this resource is not available from the Research Repository.
Export
Diykh, Mohammed 
ORCID: https://orcid.org/0000-0003-0018-4199, Miften, FS ORCID: https://orcid.org/0000-0002-3557-2194, Abdullaf, Shahab, Deo, Ravinesh C, Siuly, Siuly ORCID: https://orcid.org/0000-0003-2491-0546, Green, Jonathan H and Oudahb, Atheer Y
(2022)
Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals.
Measurement, 190.
ISSN 0263-2241
Dimensions Badge
Altmetric Badge
| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/45465 |
| DOI | 10.1016/j.measurement.2022.110731 |
| Official URL | https://www.sciencedirect.com/science/article/pii/... |
| Subjects | Current > FOR (2020) Classification > 4006 Communications engineering Current > FOR (2020) Classification > 4602 Artificial intelligence Current > FOR (2020) Classification > 4605 Data management and data science Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | seizure detection; electroencephalography; Morse Wavelet; local binary pattern algorithm; graph-based community detection algorithm; classification |
| Citations in Scopus | 13 - View on Scopus |
| Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)