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Impact of Signal Preprocessing on the Inverse Localization of the Origin of Ventricular Pacing

Jana Svehlikova, Jan Zelinka, Yesim Serinagaoglu Dogrusoz, Wilson Good, Milan Tysler, Laura Bear
2018 2018 Computing in Cardiology Conference (CinC)  
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

Qurat-ul-ain Mastoi, Teh Ying Wah, Mazin Abed Mohammed, Uzair Iqbal, Seifedine Kadry, Arnab Majumdar, Orawit Thinnukool
2022 Life  
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

Wei Yan, Zhen Zhang, Kaijian Xia
2021 Journal of Healthcare Engineering  
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

Matthijs Cluitmans, Dana H. Brooks, Rob MacLeod, Olaf Dössel, María S. Guillem, Peter M. van Dam, Jana Svehlikova, Bin He, John Sapp, Linwei Wang, Laura Bear
2018 Frontiers in Physiology  
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

Konstantin Ushenin, Vitaly Kalinin, Sukaynat Gitinova, Oleg Sopov, Olga Solovyova
2021 PLoS ONE  
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

Vassil B. Traykov, Robert Pap, Laszlo Saghy
2012 Current Cardiology Reviews  
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

Z. Zidelmal, A. Amirou, D. Ould-Abdeslam, J. Merckle
2013 Computer Methods and Programs in Biomedicine  
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

Rongru Wan, Yanqi Huang, Xiaomei Wu
2021 Sensors  
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]

Shuo Wang, Surya Nepal, Carsten Rudolph, Marthie Grobler, Shangyu Chen, Tianle Chen
2020 arXiv   pre-print
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

Huifang Huang, Jie Liu, Qiang Zhu, Ruiping Wang, Guangshu Hu
2014 BioMedical Engineering OnLine  
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

Luca Mainardi, Leif Sörnmo, Sergio Cerutti
2008 Synthesis Lectures on Biomedical Engineering  
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

Yan He, Bin Fu, Jian Yu, Renfa Li, Rucheng Jiang
2020 Applied Sciences  
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

Jaume Coll-Font, Dana H. Brooks
2018 Frontiers in Physiology  
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

Mark Nothstein, Armin Luik, Amir Jadidi, Jorge Sánchez, Laura A. Unger, Eike M. Wülfers, Olaf Dössel, Gunnar Seemann, Claus Schmitt, Axel Loewe
2021 Frontiers in Physiology  
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

Eduardo José da S. Luz, William Robson Schwartz, Guillermo Cámara-Chávez, David Menotti
2016 Computer Methods and Programs in Biomedicine  
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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