A review of time–frequency matched filter design with application to seizure detection in multichannel newborn EEG |
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| Affiliation: | 1. Department of Electrical Engineering, Qatar University, Doha, Qatar;2. The University of Queensland, Centre for Clinical Research and Perinatal Research Centre, Royal Brisbane & Women''s Hospital, Herston, QLD 4029, Australia;3. Department of Electrical Engineering, Razi University, Kermanshah, Iran;1. Laboratory for the Study of Emotion Elicitation and Expression, Department of Psychology, University of Geneva, Geneva, Switzerland;2. Swiss Center for Affective Sciences, University of Geneva, Switzerland;1. Department of Development and Regeneration, University Hospitals Leuven, Neonatal Intensive Care Unit, KU Leuven (University of Leuven), Leuven, Belgium;2. Division STADIUS, Department of Electrical Engineering (ESAT), KU Leuven (University of Leuven), Leuven, Belgium;3. Faculty of Technical Science, Singidunum University, Belgrade, Serbia;4. Department of Development and Regeneration, University Hospitals Leuven, Child Neurology, KU Leuven (University of Leuven), Leuven, Belgium;5. Section of Clinical Neurophysiology, Department of Neurology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands;6. Division of Neurology, Department of Medicine, McMaster University, Hamilton, Canada;7. Imec KU Leuven Medical IT Department, Leuven, Belgium;8. Section of Neonatology, Department of Pediatrics, Sophia Children''s Hospital, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands;9. Section of Neonatology, ZNA Middelheim, Antwerp, Belgium;10. Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK;1. Dept. of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany;2. Dept. of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany;1. School of Mechatronic Engineering, University Malaysia Perlis, 02600 Perlis, Malaysia;2. School of Microelectronic Engineering, University Malaysia Perlis, 02600 Perlis, Malaysia |
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| Abstract: | This paper presents a novel design of a time–frequency (t–f) matched filter as a solution to the problem of detecting a non-stationary signal in the presence of additive noise, for application to the detection of newborn seizure using multichannel EEG signals. The solution reduces to two possible t–f approaches that use a general formulation of t–f matched filters (TFMFs) based on the Wigner–Ville and cross Wigner–Ville distributions, and a third new approach based on the signal ambiguity domain representation; referred to as Radon-ambiguity detector. This contribution defines a general design formulation and then implements it for newborn seizure detection using multichannel EEG signals. Finally, the performance of different TFMFs is evaluated for different t–f kernels in terms of classification accuracy using real newborn EEG signals.Experimental results show that the detection method which uses TFMFs based on the cross Wigner–Ville distribution outperforms other approaches including the existing TFMF-based ones. The results also show that TFMFs which use high-resolution kernels such as the modified B-distribution, achieve higher detection accuracies compared to the ones which use other reduced-interference t–f kernels. |
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| Keywords: | Time–frequency analysis Matched filter Newborn seizure detection Multichannel EEG |
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