Vaclav Gerla
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Multivariate analysis of full-term neonatal polysomnographic data
V Gerla, K Paul, L Lhotska, V Krajca
IEEE Transactions on Information Technology in Biomedicine 13 (1), 104-110, 2008
Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal electroencephalography investigation
KL Dell, DE Payne, V Kremen, MI Maturana, V Gerla, P Nejedly, ...
EClinicalMedicine 37, 2021
Automatic identification of artifacts and unwanted physiologic signals in EEG and EOG during wakefulness
V Gerla, V Kremen, N Covassin, L Lhotska, EA Saifutdinova, J Bukartyk, ...
Biomedical Signal Processing and Control 31, 381-390, 2017
Binary social impact theory based optimization and its applications in pattern recognition
M Macaš, AP Bhondekar, R Kumar, R Kaur, J Kuzilek, V Gerla, L Lhotská, ...
Neurocomputing 132, 85-96, 2014
Neonatal EEG sleep stages modelling by temporal profiles
V Krajča, S Petránek, J Mohylová, K Paul, V Gerla, L Lhotská
Computer Aided Systems Theory–EUROCAST 2007: 11th International Conference …, 2007
Multichannel analysis of the newborn EEG data
V Gerla, L Lhotska, V Krajca, K Paul
Automated analysis of long-term eeg signals
V Gerla
doctor thesis. The Czech Technical University in Prague, 2012
Identifying seizure risk factors: A comparison of sleep, weather, and temporal features using a Bayesian forecast
DE Payne, KL Dell, PJ Karoly, V Kremen, V Gerla, L Kuhlmann, ...
Epilepsia 62 (2), 371-382, 2021
Classification of the emotional states based on the EEG signal processing
M Macaš, M Vavrecka, V Gerla, L Lhotská
2009 9th International Conference on Information Technology and Applications …, 2009
Newborn sleep stage classification using hybrid evolutionary approach
V Gerla, M Bursa, L Lhotska, K Paul, V Krajca
Int. J. Bioelectromagn 9 (1), 25-26, 2007
Iterative expert-in-the-loop classification of sleep PSG recordings using a hierarchical clustering
V Gerla, V Kremen, M Macas, D Dudysova, A Mladek, P Sos, L Lhotska
Journal of Neuroscience Methods 317 (1), 61-70, 2019
An unsupervised multichannel artifact detection method for sleep EEG based on Riemannian geometry
E Saifutdinova, M Congedo, D Dudysova, L Lhotska, J Koprivova, V Gerla
Sensors 19 (3), 602, 2019
PSGLab Matlab toolbox for polysomnographic data processing: Development and practical application
V Gerla, V Djordjevic, L Lhotska, V Krajca
Proceedings of the 10th IEEE International Conference on Information …, 2010
Feature extraction and classification of EEG sleep recordings in newborns
V Djordjevic, N Reljin, V Gerla, L Lhotska, V Krajca
2009 9th International Conference on Information Technology and Applications …, 2009
P01-Comparison of short-time Fourier transform and continuous wavelet transform for frequency analysis of sleep EEG
V Gerla, E Saifutdinova, M Macas, A Mladek, L Lhotska
Clinical Neurophysiology 129 (4), e14, 2018
System approach to complex signal processing task
V Gerla, V Djordjevic, L Lhotska, V Krajca
Computer Aided Systems Theory-EUROCAST 2009: 12th International Conference …, 2009
Prediction of shunt responsiveness in suspected patients with normal pressure hydrocephalus using the lumbar infusion test: a machine learning approach
A Mládek, V Gerla, P Skalický, A Vlasák, A Zazay, L Lhotská, V Beneš Sr, ...
Neurosurgery 90 (4), 407-418, 2022
Active learning for semiautomatic sleep staging and transitional eeg segments
M Macas, N Grimova, V Gerla, L Lhotska, E Saifutdinova
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018
EEG data mining using PCA
L Lhotská, V Krajca, J Mohylová, S Petránek, V Gerla
Data Mining and Medical Knowledge Management: Cases and Applications, 161-180, 2009
Artifact detection in multichannel sleep eeg using random forest classifier
E Saifutdinova, DU Dudysová, L Lhotská, V Gerla, M Macaš
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018
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