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Impact of Signal Preprocessing on the Inverse Localization of the Origin of Ventricular Pacing
2018
2018 Computing in Cardiology Conference (CinC)
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The origin of ventricular activity was assessed by the inverse solution using a single dipole. The impact of pre-processing on the quality of the inverse solution was observed. ...
The localization error between the known position of the stimulating electrode and the computed origin of ventricular activation was more than 5 cm if the baseline of the processed signal did not coincide ...
Acknowledgements The study was performed within the ECGI Preprocessing Group, all authors contributed equally. ...
doi:10.22489/cinc.2018.315
dblp:conf/cinc/SvehlikovaZDGTB18
fatcat:lijlpkecyjecxg5fwr4vsk4qi4
Novel DERMA Fusion Technique for ECG Heartbeat Classification
2022
Life
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The focus of this study is to classify five different types of heartbeats, including premature ventricular contraction (PVC), left bundle branch block (LBBB), right bundle branch block (RBBB), PACE, and ...
Prior to the classification, extensive experiments on feature extraction were performed to identify the specific events from ECG signals, such as P, QRS complex, and T waves. ...
Acknowledgments: This research work was partially supported by University of Malaya and Chiang Mai University.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/life12060842
pmid:35743873
fatcat:yq7ejdtatng6dhnld7ahwylqyq
Online Automatic Diagnosis System of Cardiac Arrhythmias Based on MIT-BIH ECG Database
2021
Journal of Healthcare Engineering
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Based on the hidden and sudden nature of the MIT-BIH ECG database signal and the small-signal amplitude, this paper constructs a hybrid model for the temporal correlation characteristics of the MIT-BIH ...
First, a combination of median filter and bandstop filter is used to preprocess the data in the ECG database with individual differences in ECG waveforms, and there are problems of feature inaccuracy and ...
Acknowledgments is work in this paper was supported by Affiliated Hospital of Youjiang Medical College for Nationalities. ...
doi:10.1155/2021/1819112
pmid:34956556
pmcid:PMC8702318
fatcat:mq5fp2fqnzffvkeii7vxrru7j4
Validation and Opportunities of Electrocardiographic Imaging: From Technical Achievements to Clinical Applications
2018
Frontiers in Physiology
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Depending on how it is formulated, ECGI allows the reconstruction of the activation and recovery sequence of the heart, the origin of premature beats or tachycardia, the anchors/hotspots of re-entrant ...
Future studies should focus on these aspects to achieve broad adoption of ECGI, but only after the technical challenges have been solved for that specific application/pathology. ...
Sciences of the National Institutes of Health (P41GM103545), the National Institutes of Health (NIH HL080093), the French government as part of the Investments of the Future program managed by the National ...
doi:10.3389/fphys.2018.01305
pmid:30294281
pmcid:PMC6158556
fatcat:clqlcwet3vdhjeolocr3a357mu
Parameter variations in personalized electrophysiological models of human heart ventricles
2021
PLoS ONE
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The accuracy of the ECG simulation varied widely in the same patient depending on the localization of the excitation origin. ...
Ten cases of focal ventricular activation were simulated using the bidomain model and the TNNP 2006 cellular model. ...
Writing -original draft: Konstantin Ushenin. Writing -review & editing: Vitaly Kalinin, Olga Solovyova. ...
doi:10.1371/journal.pone.0249062
pmid:33909606
pmcid:PMC8081243
fatcat:gcxdigeyvneptpwfzbwby7unfm
Frequency Domain Mapping of Atrial Fibrillation - Methodology, Experimental Data and Clinical Implications
2012
Current Cardiology Reviews
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Using frequency domain analysis to represent the rate of atrial activation by DF can avoid some of the limitations of time domain analysis of signals during AF. ...
The concept of dominant frequency (DF) has been used as a way to express local atrial activation rate during atrial fibrillation (AF). ...
In a perfectly regular signal the frequency spectrum would consist of one narrow DF peak equalling the inverse value of the signal CL and some other lower power peaks. ...
doi:10.2174/157340312803217229
pmid:22935020
pmcid:PMC3465829
fatcat:mntkwajyqfft7gl5qwmkpoielq
ECG beat classification using a cost sensitive classifier
2013
Computer Methods and Programs in Biomedicine
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After ECG preprocessing, the QRS complexes are detected and segmented. ...
An SVM follows to classify the feature vectors. Our decision rule uses dynamic reject thresholds following the cost of misclassifying a sample and the cost of rejecting a sample. ...
The denoised signal is recovered by taking the Inverse Discret Wavelet Transform (IDWT) of the resulting coefficients. ...
doi:10.1016/j.cmpb.2013.05.011
pmid:23849928
fatcat:36h3j4bebvc4bbvv6kcbyxzlwy
Detection of Ventricular Fibrillation Based on Ballistocardiography by Constructing an Effective Feature Set
2021
Sensors
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This study aimed to develop an algorithm for the automatic detection of VF based on the acquisition of cardiac mechanical activity-related signals, namely ballistocardiography (BCG), by non-contact sensors ...
Ventricular fibrillation (VF) is a type of fatal arrhythmia that can cause sudden death within minutes. The study of a VF detection algorithm has important clinical significance. ...
Conflicts of Interest: The authors declare no conflict of interest. Sensors 2021, 21, 3524 ...
doi:10.3390/s21103524
pmid:34069374
fatcat:lwme6onsevfufhhqeurokw7q5a
Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models
[article]
2020
arXiv
pre-print
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and 27.1%-56.1% attack success rate on trojaned image and time series inputs respectively in the presence of pruning-based and/or retraining-based defenses. ...
In this paper, we demonstrate a backdoor threat to transfer learning tasks on both image and time-series data leveraging the knowledge of publicly accessible Teacher models, aimed at defeating three commonly-adopted ...
contraction
beat (PVC)
paced beat
(PAB)
ventricular
escape
beat (VEB)
Original Learning System
Manipulated Learning System
Trigger
+
Trigger
+
TABLE 1 1 Comparison of Adversary ...
arXiv:2001.03274v2
fatcat:ojctk2rbpfcm3exrcaipcjirre
A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals
2014
BioMedical Engineering OnLine
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The performance of the classification system is often unsatisfactory with respect to the ventricular ectopic beat (VEB) and supraventricular ectopic beat (SVEB). ...
Meanwhile, the effect of different lead configurations on the classification results was evaluated. ...
information from the original signal, thereby facilitating accurate recovery of that original signal. ...
doi:10.1186/1475-925x-13-90
pmid:24981916
pmcid:PMC4085082
fatcat:z6a3gtsnorel5i2c2mk2lk3dpq
Understanding Atrial Fibrillation: The Signal Processing Contribution, Part II
2008
Synthesis Lectures on Biomedical Engineering
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The successive chapters are dedicated to the analysis of atrial signals recorded on the body surface and to the quantification of ventricular response. ...
Research on atrial fibrillation has stimulated the development of a wide range of signal processing tools to better understand the mechanisms ruling its initiation, maintenance, and termination. ...
ACKNOWLEDGEMENTS This book was made possible because of the collaboration between scientists who have made contributions to atrial fibrillation research. ...
doi:10.2200/s00153ed1v01y200809bme025
fatcat:twrggrnzcbcitpadlthlip253u
Efficient Learning of Healthcare Data from IoT Devices by Edge Convolution Neural Networks
2020
Applied Sciences
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datasets to evaluate the effectiveness of the deep learning model of ECG classification based on EdgeCNN. ...
the issue for agile learning of healthcare data from IoT devices. (2) We present an effective deep learning model for electrocardiogram (ECG) inference, which can be deployed to run on edge smart devices ...
Since the length of the ECG signal in the dataset is different, we preprocess the original data, splitting the ECG data and inputing the model with one-dimensional data. ...
doi:10.3390/app10248934
fatcat:qiihzqxn5ba7lhvecczdbizmqu
Tracking the Position of the Heart From Body Surface Potential Maps and Electrograms
2018
Frontiers in Physiology
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Our results show a consistent decrease in error of both simulated body surface potentials and inverse reconstructed heart surface potentials after re-localizing the heart based on our estimated geometric ...
Here, we propose an algorithm to localize the position of the heart using electrocardiographic recordings on both the heart and torso surface over a sequence of cardiac cycles. ...
ACKNOWLEDGMENTS We would like to thank the experimenters at the CardioVascular Research and Training Institute at the University of Utah for providing the canine data used in this work. ...
doi:10.3389/fphys.2018.01727
pmid:30559678
pmcid:PMC6287036
fatcat:xgqoyeumwnbl3kkh7xzdqxwxyu
CVAR-Seg: An Automated Signal Segmentation Pipeline for Conduction Velocity and Amplitude Restitution
2021
Frontiers in Physiology
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The automatic segmentation performance of the CVAR-Seg pipeline was evaluated on 37 synthetic datasets with decreasing signal-to-noise ratios. ...
Elimination of the stimulation artifact by a matched filter allowed detection of local activation times in temporal proximity. ...
Signal processing solutions would most likely also impact atrial activity morphology. ...
doi:10.3389/fphys.2021.673047
pmid:34108887
pmcid:PMC8181407
fatcat:bdyh3na2wrflti7bscge4u2d7q
ECG-based heartbeat classification for arrhythmia detection: A survey
2016
Computer Methods and Programs in Biomedicine
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The authors also would like to thank the reviewers and the editors for their valuable comments and contributions that helped to increase significantly the readability and organization of the present survey ...
Acknowledgments The authors would like to thank UFOP, UFMG, UFPR, FAPEMIG, CAPES and CNPq for the financial support. ...
contraction
Ventricular
E
Ventricular escape beat
ectopic beat
F
F
Fusion of ventricular
Fusion beat
and normal beat
Q
P ou /
Paced beat
Unknown beat
f
Fusion of paced and normal beat ...
doi:10.1016/j.cmpb.2015.12.008
pmid:26775139
fatcat:2rb6cwyivvh2tixqnwaanx6ery
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