V. Gerla

发表

Frames of reference and their neural correlates within navigation in a 3D environment

M. Vavrecka, V. Gerla, L. Lhotská, 2012, Visual Neuroscience.

Noninvasive assessment of cardiac output by brachial occlusion-cuff technique: comparison with the open-circuit acetylene washin method.

Bruce D. Johnson, V. Kremen, V. Gerla, 2016, Journal of applied physiology.

EEG Analysis of the Navigation Strategies in a 3D Tunnel Task

Lenka Lhotská, Michal Vavrecka, Václav Gerla, 2011, ICONIP.

Detecting Sleep Spindles Using Entropy

V. Gerla, L. Lhotská, G. Manis, 2020 .

Adaptive Segmentation Optimization for Sleep Spindle Detector

V. Gerla, L. Lhotská, M. Macas, 2016, ITBAM.

Inductive Modeling in Newborn Sleep Stage Recognition

P. Kordík, V. Gerla, L. Lhotská, 2022 .

For Peer Review 1 Frames of reference and their neural correlates within navigation in a 3 D environment

M. Vavrecka, V. Gerla, L. Lhotská, 2012 .

Optimal Parameters of Adaptive Segmentation for Epileptic Graphoelements Recognition

V. Krajca, V. Gerla, L. Lhotská, 2017 .

Neonatal EEG Sleep Stages Modelling by Temporal Profiles

Lenka Lhotská, Vladimir Krajca, Jitka Mohylová, 2007, EUROCAST.

Newborn Sleep Stage Classification Using Hybrid Evolutionary Approach

Vladimir Krajca, Lenka Lhotska, Vaclav Gerla, 2007 .

An Unsupervised Multichannel Artifact Detection Method for Sleep EEG Based on Riemannian Geometry

Lenka Lhotská, Marco Congedo, Václav Gerla, 2019, Sensors.

Artifact Detection in Multichannel Sleep EEG using Random Forest Classifier

Lenka Lhotská, Martin Macas, Václav Gerla, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Binary social impact theory based optimization and its applications in pattern recognition

Rishemjit Kaur, Ritesh Kumar, Amol P. Bhondekar, 2014, Neurocomputing.

Prediction of Shunt Responsiveness in Suspected Patients With Normal Pressure Hydrocephalus Using the Lumbar Infusion Test: A Machine Learning Approach

V. Gerla, L. Lhotská, O. Bradáč, 2022, Neurosurgery.

Semi-Automated Sleep EEG Scoring with Active Learning and HMM-Based Deletion of Ambiguous Instances

Lenka Lhotska, Vaclav Gerla, Nela Grimova, 2019, UCAmI.

Active Learning for Semiautomatic Sleep Staging and Transitional EEG Segments

Lenka Lhotská, Martin Macas, Václav Gerla, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Identifying seizure risk factors: A comparison of sleep, weather, and temporal features using a Bayesian forecast

L. Kuhlmann, G. Worrell, V. Kremen, 2020, Epilepsia.

Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal electroencephalography investigation

A. Burkitt, L. Kuhlmann, B. Brinkmann, 2021, EClinicalMedicine.

Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal EEG investigation.

A. Burkitt, L. Kuhlmann, B. Brinkmann, 2021, medRxiv.

Automatic identification of artifacts and unwanted physiologic signals in EEG and EOG during wakefulness

Lenka Lhotská, Václav Gerla, Elizaveta Saifutdinova, 2017, Biomed. Signal Process. Control..

Semi-automated detection of polysomnographic REM sleep without atonia (RSWA) in REM sleep behavioral disorder

Lenka Lhotská, Václav Gerla, Iva Milerska, 2019, Biomed. Signal Process. Control..

Iterative expert-in-the-loop classification of sleep PSG recordings using a hierarchical clustering

V Gerla, V. Kremen, M. Macas, 2019, Journal of Neuroscience Methods.

Expert-in-the-loop Learning for Sleep EEG Data

Lenka Lhotská, Martin Macas, Václav Gerla, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Hybrid Hierarchical Clustering Algorithm Used for Large Datasets: A Pilot Study on Long-Term Sleep Data

Vaclav Gerla, Elizaveta Saifutdinova, Martin Macas, 2017, BHI 2017.

Riemannian Geometry in Sleep Stage Classification

Lenka Lhotská, Václav Gerla, Elizaveta Saifutdinova, 2017, ITBAM.

EEG Data Mining Using PCA

Vladimir Krajca, Jitka Mohylová, Svojmil Petránek, 2009 .

Detection of Sleep Stages in Temporal Profiles in Neonatal EEG—k-NN versus k-Means Approach: A Feasibility Study

Vladimir Krajca, Lenka Lhotska, Vaclav Gerla, 2018, IFMBE Proceedings.

Classification of the emotional states based on the EEG signal processing

M. Macas, V. Gerla, L. Lhotska, 2009, 2009 9th International Conference on Information Technology and Applications in Biomedicine.

From head micro-motions towards CSF dynamics and non-invasive intracranial pressure monitoring

Helen Whitley, P. Seba, V. Gerla, 2021, Scientific Reports.

PSGLab Matlab toolbox for polysomnographic data processing: Development and practical application

Vladimir Krajca, Lenka Lhotska, Vladana Djordjevic, 2010, Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine.

Addressing the Cold Start Problem in Active Learning Approach Used For Semi-automated Sleep Stages Classification

Martin Macas, Václav Gerla, Nela Grimova, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Boosting phase-contrast MRI performance in idiopathic normal pressure hydrocephalus diagnostics by means of machine learning approach.

Helen Whitley, V. Gerla, L. Lhotská, 2022, Neurosurgical focus.

Multimedia support in the field of interdisciplinary education

Vladimir Krajca, Lenka Lhotska, Michal Huptych, 2009, 2009 EAEEIE Annual Conference.

Visualization methods used for evaluation of neonatal polysomnographic data

Vladimir Krajca, Lenka Lhotska, Vladana Djordjevic, 2009, 2009 9th International Conference on Information Technology and Applications in Biomedicine.

Sleep spindles detection using Empirical Mode Decomposition

Lenka Lhotská, Václav Gerla, Elizaveta Saifutdinova, 2015, 2015 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM).

System Approach to Complex Signal Processing Task

Lenka Lhotská, Vladimir Krajca, Vladana Djordjevic, 2009, EUROCAST.

Multivariate Analysis of Full-Term Neonatal Polysomnographic Data

Lenka Lhotská, Vladimir Krajca, Karel Paul, 2009, IEEE Transactions on Information Technology in Biomedicine.