Objective.The aim of this study is to create a database for the development, evaluation and objective comparison of algorithms for P wave detection in ECG signals.BrnoUniversity ofTechnology ECG SignalDatabase with Annotations ofP-Wave (BUT PDB) is an ECG signal database with marked peaks of P waves annotated by ECG experts. Currently, there are only a few databases of pathological ECG signals with P-wave annotations, and some are incorrect.Approach.The pathological ECG signals used in this work were selected from three existing databases of ECG signals: MIT-BIH Arrhythmia Database, MIT-BIH Supraventricular Arrhythmia Database and Long Term AF Database. The P-wave positions were manually annotated by two ECG experts in all selected signals.Main results.The final BUT PDB composed of selected signals consists of 50 two-minute, two-lead pathological ECG signal records with annotated P waves. Each record also contains a description of the diagnosis (pathology) present in the selected part of the record and information about positions and types of QRS complexes.Significance.The BUT PDB is created for developing new, more accurate and robust methods for P wave detection. These algorithms will be used in medical practice and will help cardiologists to evaluate ECG records, establish diagnoses and save time.
BACKGROUND: Spatial and temporal resolution of brain network activity can be improved by combining different modalities. Functional Magnetic Resonance Imaging (fMRI) provides full brain coverage with limited temporal resolution, while electroencephalography (EEG), estimates cortical activity with high temporal resolution. Combining them may provide improved network characterization. NEW METHOD: We examined relationships between EEG spatiospectral pattern timecourses and concurrent fMRI BOLD signals using canonical hemodynamic response function (HRF) with its 1st and 2nd temporal derivatives in voxel-wise general linear models (GLM). HRF shapes were derived from EEG-fMRI time courses during "resting-state", visual oddball and semantic decision paradigms. RESULTS: The resulting GLM F-maps self-organized into several different large-scale brain networks (LSBNs) often with different timing between EEG and fMRI revealed through differences in GLM-derived HRF shapes (e.g., with a lower time to peak than the canonical HRF). We demonstrate that some EEG spatiospectral patterns (related to concurrent fMRI) are weakly task-modulated. COMPARISON WITH EXISTING METHOD(S): Previously, we demonstrated 14 independent EEG spatiospectral patterns within this EEG dataset, stable across the resting-state, visual oddball and semantic decision paradigms. Here, we demonstrate that their time courses are significantly correlated with fMRI dynamics organized into LSBN structures. EEG-fMRI derived HRF peak appears earlier than the canonical HRF peak, which suggests limitations when assuming a canonical HRF shape in EEG-fMRI. CONCLUSIONS: This is the first study examining EEG-fMRI relationships among independent EEG spatiospectral patterns over different paradigms. The findings highlight the importance of considering different HRF shapes when spatiotemporally characterizing brain networks using EEG and fMRI.
- MeSH
- dospělí MeSH
- elektroencefalografie metody MeSH
- funkční zobrazování neurálních procesů metody MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- mladý dospělý MeSH
- nervová síť diagnostické zobrazování fyziologie MeSH
- neurovaskulární vazba fyziologie MeSH
- psycholingvistika MeSH
- velký mozek diagnostické zobrazování fyziologie MeSH
- zraková percepce fyziologie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
A spectrogram reflects the arrangement of nucleotides through the whole chromosome or genome. Our previous study suggested that the spectrogram of whole genome DNA sequences is a suitable tool for the determination of relationships among bacteria. Related bacteria have similar spectrograms, and similarity in spectrograms was measured using a color layout descriptor. Several parameters, such as the mapping of four bases into a spectrogram, the number of considered elements in the color layout descriptor, the color model of the image and the building tree method, can be changed. This study addresses the use of parameter selection to ensure the best classification results. The quality of the classification was measured by Matthew's correlation coefficient (MCC). The proposed method with optimal parameters (called SpectCMP-Spectrogram CoMParison method) achieved an average MCC of 0.73 at the phylum level. The SpectCMP method was also tested at the order level; the average MCC in the classification of class Gammaproteobacteria was 0.76. The success of a classification with respect to the correct phyla was compared to three methods that are used in bacterial phylogeny: the CVTree method, OGTree method and moment vector method. The results show that the SpectCMP method can be used in bacterial classification at various taxonomic levels.
