arXiv subjects

Tomasz Gradowski

Publications and source records attributed to Tomasz Gradowski.

7 recordsLinked to original sources

arXiv2026

A novel method for analysis of transient morphological changes in quasiperiodic physiological signals and their neurogenic correlates

Conventional ECG visualization and analysis methods typically emphasize either waveform morphology or rhythm variability. This work presents a visualization framework for quasiperiodic physiological signals that enables simultaneous assessment of beat-to-beat morphological changes and rhythm dynamics in a single representation. The proposed method converts quasiperiodic signals into two-dimensional carpet plots. Characteristic events (e.g., ECG R peaks) are used to align consecutive signal segments, which are transformed into color-coded rows and stacked in chronological order. The resulting image preserves both the temporal evolution of signal morphology and variations in cycle duration. The method was evaluated using ECG recordings from multiple publicly available databases containing healthy subjects and patients with diverse cardiac abnormalities, as well as synchronized multimodal physiological recordings. Carpet plots enabled rapid visualization of transient morphological changes alongside heart rate dynamics across recordings ranging from several minutes to hours. The representation highlighted clinically relevant phenomena, including ST segment alterations, QT interval variability, changes in T wave morphology, atrial fibrillation episodes, premature ventricular complexes, Wenckebach periodicity, and stress-test phase transitions. The image-based representation was also shown to be suitable for automated analysis using convolutional neural network feature extraction. Carpet plots provide a compact representation of quasiperiodic physiological signals, jointly visualizing rhythm and morphology across long-term recordings. The proposed framework facilitates both expert interpretation and image-based computational analysis, offering a general approach for investigating transient physiological phenomena in ECG and other synchronized quasiperiodic signals.

physics.med-ph↗

arXiv2025

Deep learning model for ECG reconstruction reveals the information content of ECG leads

This study introduces a deep learning model based on the U-net architecture to reconstruct missing leads in electrocardiograms (ECGs). The model was trained to reconstruct 12-lead ECG data from reduced lead configurations using publicly available datasets. The results highlight the ability of the model to quantify the information content of each ECG lead and its inter-lead correlations. This has significant implications for optimizing lead selection in diagnostic scenarios, particularly in settings where complete 12-lead ECGs are impractical. In addition, the study provides insights into the physiological underpinnings of ECG signals and their propagation. The findings pave the way for advances in telemedicine, portable ECG devices, and personalized cardiac diagnostics by reducing redundancy and improving signal interpretation.

eess.SP↗

arXiv2024

Physically motivated projection of the electrocardiogram -- a feasibility study

We present PhysECG: a physically motivated projection of the 12 lead electrocardiogram, supported by a deep learning model trained on 21,799 recordings from the PTB-XL database and discuss its feasibility. The method allows to evaluate the epicardial activity (inverse problem of ECG imaging) and, in particular, to distinguish left and right ventricular activity, with statistical spread related to localization of the septum. The observed dyssynchrony resembles other experimental results. The foundations of the method are based on the molecular theory of biopotentials. The heart's activity in view of the method is decomposed into two processes: the passage of the electric activation wavefront and the response of cardiomyocytes. We introduce the idea of the electrode-resolved activity function, which represents the mass of the ventricle in Phase 0 of action potential within the lead field of each electrode. The computations are fast and robust, with excellent convergence. We present the quality metrics for the reconstruction based on the model on the testing set selected from the PTB database. In order to prove feasibility, we present and discuss two healthy controls: male and female, and two pathologies: right bundle branch block, and anterior myocardial infarction. The results obtained using PhysECG seem to be in accordance with the changes evoked by pathology, which has to be confirmed by subsequent clinical studies. The method is based on ECG, and does not require reconstruction of body geometry, which presents an affordable solution for low and middle-income countries where access to imaging is limited.

physics.med-ph↗

arXiv2024

$Q$-voter model with independence on signed random graphs: approximate master equations

Approximate master equations are derived for the two-state $q$-voter model with independence on signed random graphs, with negative and positive weights of links corresponding to antagonistic and reinforcing interactions, respectively. Depending on the mean degree of nodes, the size of the $q$-neighborhood, and the fraction of the antagonistic links, with decreasing independence of agents, this model shows a first- or second-order ferromagnetic-like transition to an ordered state with one dominant opinion. Predictions of the approximate master equations concerning this transition exhibit quantitative agreement with results of Monte Carlo simulations in the whole range of parameters of the model, even if predictions of the widely used pair and mean field approximations are inaccurate. Heterogeneous pair approximation derived from the approximate master equations yields results indistinguishable from homogeneous pair approximation studied before and fails in the case of the model on networks with a small and comparable mean degree of nodes and size of the $q$-neighborhood.

cond-mat.stat-mech↗

arXiv2023

$Q$-voter model with independence on signed random graphs: homogeneous approximations

The $q$-voter model with independence is generalized to signed random graphs and studied by means of Monte Carlo simulations and theoretically using the mean field approximation and different forms of the pair approximation. In the signed network with quenched disorder, positive and negative signs associated randomly with the links correspond to reinforcing and antagonistic interactions, promoting, respectively, the same or opposite orientations of two-state spins representing agents' opinions; otherwise, the opinions are called mismatched. With probability $1-p$, the agents change their opinions if the opinions of all members of a randomly selected $q$-neighborhood are mismatched, and with probability $p$, they choose an opinion randomly. The model on networks with finite mean degree $\langle k \rangle$ and fixed fraction of the antagonistic interactions $r$ exhibits ferromagnetic transition with varying the independence parameter $p$, which can be first- or second-order, depending on $q$ and $r$, and disappears for large $r$. Besides, numerical evidence is provided for the occurrence of the spin-glass-like transition for large $r$. The order and critical lines for the ferromagnetic transition on the $p$ vs. $r$ phase diagram obtained in Monte Carlo simulations are reproduced qualitatively by the mean field approximation. Within the range of applicability of the pair approximation, for the model with $\langle k \rangle$ finite but $\langle k \rangle \gg q$, predictions of the homogeneous pair approximation concerning the ferromagnetic transition show much better quantitative agreement with numerical results for small $r$ but fail for larger $r$. A more advanced signed homogeneous pair approximation is formulated which distinguishes between classes of active links with a given sign connecting nodes occupied by agents with mismatched opinions...

cond-mat.stat-mech↗

arXiv2023

The $q$-neighbor Ising model on multiplex networks with partial overlap of nodes

The $q$-neighbor Ising model for the opinion formation on multiplex networks with two layers in the form of random graphs (duplex networks), the partial overlap of nodes, and LOCAL\&AND spin update rule was investigated by means of the pair approximation and approximate Master equations as well as Monte Carlo simulations. Both analytic and numerical results show that for different fixed sizes of the $q$-neighborhood and finite mean degrees of nodes within the layers the model exhibits qualitatively similar critical behavior as the analogous model on multiplex networks with layers in the form of complete graphs. However, as the mean degree of nodes is decreased the discontinuous ferromagnetic transition, the tricritical point separating it from the continuous transition and the possible coexistence of the paramagnetic and ferromagnetic phases at zero temperature occur for smaller relative sizes of the overlap. Predictions of the simple homogeneous pair approximation concerning the critical behavior of the model under study show good qualitative agreement with numerical results; predictions based on the approximate Master equations are usually quantitatively more accurate, but yet not exact. Two versions of the heterogeneous pair approximation are also derived for the model under study, which, surprisingly, yield predictions only marginally different or even identical to those of the simple homogeneous pair approximation. In general, predictions of all approximations show better agreement with the results of Monte Carlo simulations in the case of continuous than discontinuous ferromagnetic transition.

cond-mat.stat-mech↗

arXiv2019

Pair approximation for the $q$-voter model with independence on multiplex networks

The $q$-voter model with independence is investigated on multiplex networks with fully overlapping layers in the form of various complex networks corresponding to different levels of social influence. Detailed studies are performed for the model on multiplex networks with two layers with identical degree distributions, obeying the LOCAL&AND and GLOBAL&AND spin update rules differing by the way in which the $q$-lobbies of neighbors within different layers exert their joint influence on the opinion of a given agent. Homogeneous pair approximation is derived for a general case of a two-state spin model on a multiplex network and its predictions are compared with results of Monte Carlo simulations of the above-mentioned $q$-voter model with independence for a broad range of parameters. As the parameter controlling the level of agents' independence is changed ferromagnetic phase transition occurs which can be first- or second-order, depending on the size of the lobby $q$. Details of this transition, e.g., position of the critical points, depend on the topology and other features, e.g., the mean degree of nodes of the layers. If the mean degree of nodes in the layers is substantially larger than the size of the $q$-lobby good agreement is obtained between numerical results and theoretical predictions based on the homogeneous pair approximation concerning the order and details of the ferromagnetic transition. In the case of the model on multiplex networks with layers in the form of homogeneous Erdo\"s-R\'enyi and random regular graphs as well as weakly heterogeneous scale-free networks this agreement is quantitative, while in the case of layers in the form of strongly heterogeneous scale-free networks it is only qualitative. If the mean degree of nodes is small and comparable with $q$ predictions of the homogeneous PA are in general even qualitatively wrong.

cond-mat.stat-mech↗