Publications
36 results found
Nicolaou N, Constandinou TG, 2016, A Nonlinear Causality Estimator Based on Non-Parametric Multiplicative Regression, FRONTIERS IN NEUROINFORMATICS, Vol: 10, ISSN: 1662-5196
Lauteslager T, Nicolaou N, Lande TS, et al., 2015, Functional neuroimaging using UWB impulse radar: A feasibility study, 11th IEEE Annual Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 406-409, ISSN: 2163-4025
Demarchou E, Georgiou J, Nicolaou N, et al., 2014, Anesthetic-induced changes in EEG activity: a graph theoretical approach, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 45-48, ISSN: 2163-4025
Nicolaou N, Georgiou J, 2014, Spatial Analytic Phase Difference of EEG activity during anesthetic-induced unconsciousness, CLINICAL NEUROPHYSIOLOGY, Vol: 125, Pages: 2122-2131, ISSN: 1388-2457
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- Citations: 2
Nicolaou N, Georgiou J, 2014, Global field synchrony during general anaesthesia, BRITISH JOURNAL OF ANAESTHESIA, Vol: 112, Pages: 529-539, ISSN: 0007-0912
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- Citations: 6
Nicolaou N, Georgiou J, 2014, Neural Network-Based Classification of Anesthesia/Awareness Using Granger Causality Features, CLINICAL EEG AND NEUROSCIENCE, Vol: 45, Pages: 77-88, ISSN: 1550-0594
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- Citations: 2
Nicolaou N, Georgiou J, 2014, The Study of EEG Dynamics During Anesthesia with Cross-Recurrence Rate, Cureus, Vol: 6
Daly I, Nicolaou N, Nasuto SJ, et al., 2013, Automated Artifact Removal From the Electroencephalogram: A Comparative Study, CLINICAL EEG AND NEUROSCIENCE, Vol: 44, Pages: 291-306, ISSN: 1550-0594
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- Citations: 13
Nicolaou N, Georgiou J, 2013, Towards automatic sleep staging via Cross-Recurrence Rate of EEG and ECG activity, IEEE BioCAS, Pages: 198-201
Nicolaou N, Georgiou J, 2013, Monitoring depth of hypnosis under propofol general anaesthesia: Granger Causality and Hidden Markov Models, Neurotechnix (special session: BrainRehab)
Garreau G, Nicolaou N, Georgiou J, 2012, Individual classification through autoregressive modelling of micro-Doppler signatures, IEEE BioCAS, Pages: 312-315
Nicolaou N, Dionysiou A, Georgiou J, 2012, Temporal dynamics of EEG during anesthesia, 12th IEEE BIBE, Pages: 288-291
Nicolaou N, Georgiou J, 2012, Detection of epileptic electroencephalogram based on Permutation Entropy and Support Vector Machines, EXPERT SYSTEMS WITH APPLICATIONS, Vol: 39, Pages: 202-209, ISSN: 0957-4174
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- Citations: 110
Nicolaou N, Houris S, Alexandrou P, et al., 2012, Permutation Entropy: a reliable measure for automatic monitoring of anesthetic depth during surgery?, Engineering Intelligent Systems Journal (Special Issue: Timely developments in Artificial Intelligence Applications), Vol: 20, Pages: 1-10
Nicolaou N, Hourris S, Alexandrou P, et al., 2012, EEG-Based Automatic Classification of 'Awake' versus 'Anesthetized' State in General Anesthesia Using Granger Causality, PLOS ONE, Vol: 7, ISSN: 1932-6203
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- Citations: 31
Garreau G, Nicolaou N, Andreou C, et al., 2011, Computationally efficient classification of human transport mode using micro-Doppler signatures, 45th CISS
Nicolaou N, Georgiou J, 2011, The use of permutation entropy to characterize sleep electroencephalograms., Clin EEG Neurosci, Vol: 42, Pages: 24-28, ISSN: 1550-0594
This work proposes the use of Permutation Entropy (PE), a measure of time-series complexity, to characterize electroencephalogram (EEG) signals recorded during sleep. Such a measure could provide information concerning the different sleep stages and, thus, be utilized as an additional aid to obtain sleep staging information. PE has been estimated for artifact-free 30s segments from more than 80 hours of EEG records obtained from 16 subjects during all-night recordings, from which the mean PE for each sleep stage was obtained. It was found that different sleep stages are characterized by significantly different PE values, which track the physiological changes in the complexity of the EEG signals observed at the different sleep stages. This finding encourages the use of PE as an additional aide to either visual or automated sleep staging.
Nicolaou N, Houris S, Alexandrou P, et al., 2011, Entropy measures for discrimination of 'awake' Vs 'anaesthetized' state in recovery from general anesthesia., Pages: 2598-2601, ISSN: 1557-170X
Approximate Entropy (ApEn) and Permutation Entropy (PE) have been recently introduced for assessment of anesthetic depth. Both measures have previously been shown to track changes in the electrical brain activity related to the administration of anesthetic agents. In this paper ApEn and PE are compared for the automatic classification of 'awake' and 'anesthetized' state using a Support Vector Machine to assess their robustness for potential use in a device for monitoring awareness during general anesthesia. It was found that both measures provide linearly separable features and we are able to discriminate between the two states with accuracy greater than 96% using either of the two entropy measures.
Nicolaou N, Houris S, Alexandrou P, et al., 2011, Cross-Recurrence Rate for discriminating 'conscious' and 'unconscious' state in propofol general anesthesia, IEEE BioCAS, Pages: 416-419
Nicolaou N, Houris S, Alexandrou P, et al., 2011, Using Granger Causality to characterise bidirectional interactions in the human brain during induction of anaesthesia, BIOSIGNALS
Nicolaou N, Houris S, Alexandrou P, et al., 2011, Permutation Entropy for discriminating ‘conscious’ and ‘unconscious’ state in general anaesthesia, Engineering Applications of Neural Networks, Editors: Iliadis, Jayne, Publisher: Springer Boston, Pages: 280-288
Demosthenous P, Nicolaou N, Georgiou J, 2010, A Hardware-efficient Lowpass filter design for biomedical applications, IEEE BioCAS, Pages: 130-133
Nicolaou N, Georgiou J, 2010, Permutation Entropy: a new feature for Brain-Computer Interfaces, IEEE BioCAS, Pages: 49-52
Nicolaou N, Georgiou J, 2009, Autoregressive model order estimation criteria for monitoring awareness during anaesthesia, Proceedings of the 5th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI'2009), Editors: Papadopoulos, Andreou, Iliadis, Maglogiannis, Publisher: Springer Berlin Heideberg, Pages: 71-80
Nicolaou N, Georgiou J, 2009, Towards a Morse Code-Based Non-invasive Though-to-Speech Converter, Biomedical Engineering Systems and Technologies, Editors: Fred, Filipe, Gamboa, Publisher: Springer-Verlag Berlin Heidelberg, Pages: 123-135
Nicolaou N, Georgiou J, Polycarpou M, 2008, Autoregressive features for a thought-to-speech converter, BIODEVICES
Nicolaou N, Nasuto SJ, Georgiou J, 2008, Single-trial Event-related potential analysis for Brain-Computer Interfaces, AISB, Pages: 13-18
Nicolaou N, Petroudi S, Georgiou J, et al., 2008, Digital mammography: towards pectoral muscle removal via Independent Component Analysis, IEE MEDSIP
Petroudi S, Nicolaou N, Georgiou J, et al., 2008, Breast abnormality detection incorporating breast density information based on Independent Component Analysis, IWDM, Pages: 667-673
Nicolaou N, Nasuto SJ, 2007, Automatic artefact removal from event-related potentials via clustering, JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, Vol: 48, Pages: 173-183, ISSN: 0922-5773
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- Citations: 11
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