Computing in cardiology最新文献_第6页

Reduction of Effects of Noise on the Inverse Problem of Electrocardiography with Bayesian Estimation. 用贝叶斯估计降低噪声对心电图反问题的影响。

Computing in cardiology Pub Date : 2018-09-01 DOI: 10.22489/CinC.2018.309

Y Serinagaoglu Dogrusoz, L R Bear, J Svehlikova, J Coll-Font, W Good, R Dubois, E van Dam, R S MacLeod

{"title":"Reduction of Effects of Noise on the Inverse Problem of Electrocardiography with Bayesian Estimation.","authors":"Y Serinagaoglu Dogrusoz, L R Bear, J Svehlikova, J Coll-Font, W Good, R Dubois, E van Dam, R S MacLeod","doi":"10.22489/CinC.2018.309","DOIUrl":"https://doi.org/10.22489/CinC.2018.309","url":null,"abstract":"To overcome the ill-posed nature of the inverse problem of electrocardiography (ECG) and stabilize the solutions, regularization is used. Despite several studies on noise, effect of prefiltering of ECG signals on the regularized inverse solutions has not been explored. We used Bayesian estimation for solving the inverse ECG problem with and without applying various prefiltering methods, and evaluated our results using experimental data that came from a Langendorff-perfused pig heart suspended in a human-shaped torso-tank. Epicardial electrograms were recorded during RV pacing using a 108-electrode array, simultaneously with ECGs from 128 electrodes embedded in the tank surface. Leave-one-beat-out protocol was used to obtain the prior probability density function (pdf) of electro-grams and noise statistics. Noise pdf was assumed to be zero mean-Gaussian, with covariance assumptions: a) independent and identically distributed (noi-iid), b) correlated (noi-corr). Reconstructed electrograms and activation times were compared to those directly recorded by the sock for 3 beats selected from the recording. Noi-corr is superior to noi-iid when the training set is a good match to data, but for applications requiring activation time derivation, careful selection of preprocessing methods, in particular to adequately remove high-frequency noise, and an appropriate noise model is needed.","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":"45 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6648701/pdf/nihms-1010743.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9523354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

The Reproducibility of Global Electrical Heterogeneity ECG Measurements. 心电图测量全局电异质性的可重复性。

Computing in cardiology Pub Date : 2018-09-01 Epub Date: 2019-06-24 DOI: 10.22489/cinc.2018.162

Erick A Perez-Alday, Christopher Hamilton, Annabel Li-Pershing, Jose M Monroy-Trujillo, Michelle Estrella, Stephen M Sozio, Bernard Jaar, Rulan Parekh, Larisa Tereshchenko

{"title":"The Reproducibility of Global Electrical Heterogeneity ECG Measurements.","authors":"Erick A Perez-Alday, Christopher Hamilton, Annabel Li-Pershing, Jose M Monroy-Trujillo, Michelle Estrella, Stephen M Sozio, Bernard Jaar, Rulan Parekh, Larisa Tereshchenko","doi":"10.22489/cinc.2018.162","DOIUrl":"https://doi.org/10.22489/cinc.2018.162","url":null,"abstract":"Background: Global electrical heterogeneity (GEH) is a useful predictor of adverse clinical outcomes. However, reproducibility of GEH measurements on 10-second routine clinical ECG is unknown.Methods: Data of the prospective cohort study of incident hemodialysis patients (n=253; mean age 54.6±13.5y; 56% male; 79% African American) were analysed. Two random 10-second segments of 5-minute ECG recording in sinus rhythm were compared. GEH was measured as spatial QRS-T angle, spatial ventricular gradient (SVG) magnitude and direction (azimuth and elevation), and a scalar value of SVG measured by (1) sum absolute QRST integral (SAI QRST), and (2) QT integral on vector magnitude signal (iVMQT). Bland-Altman analysis was used to calculate agreement.Results: For all studied vectorcardiographic metrics, agreement was substantial (Lin's concordance coefficient >0.98), and precision was perfect (>99.99%). 95% limits of agreement were ±14° for spatial QRS-T angle, ±13° for SVG azimuth, ±4° for SVG elevation, ±14 mV*ms for SVG magnitude, and ±17 mV*ms for SAI QRST. SAI QRST and iVMQT were in substantial agreement with each other.Conclusion: Reproducibility of a 10-second automated GEH ECG measurements was substantial, and precision was perfect.","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7158900/pdf/nihms-1032512.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37840715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Common-Ground Review of the Potential for Machine Learning Approaches in Electrocardiographic Imaging Based on Probabilistic Graphical Models. 基于概率图形模型的心电图成像中机器学习方法的潜力综述。

Computing in cardiology Pub Date : 2018-09-01 DOI: 10.22489/CinC.2018.348

Jaume Coll-Font, Linwei Wang, Dana H Brooks

引用次数: 0

Global Electrical Heterogeneity: Mechanisms and Clinical Significance. 全球电异质性:机制和临床意义。

Computing in cardiology Pub Date : 2018-09-01 Epub Date: 2019-06-24 DOI: 10.22489/cinc.2018.165

Larisa G Tereshchenko

{"title":"Global Electrical Heterogeneity: Mechanisms and Clinical Significance.","authors":"Larisa G Tereshchenko","doi":"10.22489/cinc.2018.165","DOIUrl":"https://doi.org/10.22489/cinc.2018.165","url":null,"abstract":"This review summarizes recent findings and discusses a clinical significance of a vectorcardiographic (VCG) Global electrical heterogeneity (GEH). GEH concept is based on the concept of the spatial ventricular gradient (SVG), which is a global measure of the dispersion of total recovery time. We quantify GEH by measuring five features of the SVG vector (SVG magnitude, direction (azimuth and elevation), a scalar value, and spatial QRS-T angle) on orthogonal XYZ ECG. In analysis of more than 20,000 adults we showed that GEH is independently associated with sudden cardiac death (SCD) after adjustment for demographics, cardiovascular disease (time-updated incident non-fatal cardiovascular events [coronary heart disease, heart failure, stroke, atrial fibrillation, use of beta-blockers], and known risk factors [cholesterol, triglycerides, physical activity index, smoking, diabetes, obesity, hypertension, anti-hypertensive medications, creatinine, alcohol intake, left ventricular ejection fraction, and time-updated ECG metrics (heart rate, QTc, QRS duration, ECG-left ventricular hypertrophy, bundle branch block or interventricular conduction delay)]. This finding suggests that GEH represents an independent electrophysiological substrate of SCD.","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7158901/pdf/nihms-1032510.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37841140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

You Snooze, You Win: the PhysioNet/Computing in Cardiology Challenge 2018. 你打盹，你就赢了:2018年心脏病学物理网络/计算挑战赛。

Computing in cardiology Pub Date : 2018-09-01 Epub Date: 2019-06-24 DOI: 10.22489/cinc.2018.049

Mohammad M Ghassemi, Benjamin E Moody, Li-Wei H Lehman, Christopher Song, Qiao Li, Haoqi Sun, Roger G Mark, M Brandon Westover, Gari D Clifford

引用次数: 107

A Multi-Scale Investigation of Global Electrical Heterogeneity: Effects of Body Habitus, Respiration, and Tissue Conductivity. 全球电异质性的多尺度研究:身体习惯、呼吸和组织电导率的影响。

Computing in cardiology Pub Date : 2018-09-01 Epub Date: 2019-06-24 DOI: 10.22489/cinc.2018.161

Erick A Perez-Alday, Haibo Ni, Christopher Hamilton, Annabel Li-Pershing, Bernard Jaar, Jose M Monroy-Trujillo, Michelle Estrella, Rulan Parekh, Henggui Zhang, Larisa Tereshchenko

引用次数: 1

Effects of ECG Signal Processing on the Inverse Problem of Electrocardiography. 心电信号处理对心电图反问题的影响。

Computing in cardiology Pub Date : 2018-09-01 DOI: 10.22489/CinC.2018.070

Laura R Bear, Y Serinagaoglu Dogrusoz, J Svehlikova, J Coll-Font, W Good, E van Dam, R Macleod, E Abell, R Walton, R Coronel, Michel Haissaguerre, R Dubois

{"title":"Effects of ECG Signal Processing on the Inverse Problem of Electrocardiography.","authors":"Laura R Bear, Y Serinagaoglu Dogrusoz, J Svehlikova, J Coll-Font, W Good, E van Dam, R Macleod, E Abell, R Walton, R Coronel, Michel Haissaguerre, R Dubois","doi":"10.22489/CinC.2018.070","DOIUrl":"https://doi.org/10.22489/CinC.2018.070","url":null,"abstract":"The inverse problem of electrocardiography is ill-posed. Errors in the model such as signal noise can impact the accuracy of reconstructed cardiac electrical activity. It is currently not known how sensitive the inverse problem is to signal processing techniques. To evaluate this, experimental data from a Langendorff-perfused pig heart (n=1) suspended in a human-shaped torso-tank was used. Different signal processing methods were applied to torso potentials recorded from 128 electrodes embedded in the tank surface. Processing methods were divided into three categories i) high-frequency noise removal ii) baseline drift removal and iii) signal averaging, culminating in n=72 different signal sets. For each signal set, the inverse problem was solved and reconstructed signals were compared to those directly recorded by the sock around the heart. ECG signal processing methods had a dramatic effect on reconstruction accuracy. In particular, removal of baseline drift significantly impacts the magnitude of reconstructed electrograms, while the presence of high-frequency noise impacts the activation time derived from these signals (p<0.05).","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6424339/pdf/nihms-1010742.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37080799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Analyzing Source Sampling to Reduce Error in ECG Forward Simulations. 分析源采样减少心电正演模拟误差。

Computing in cardiology Pub Date : 2017-09-01 Epub Date: 2018-04-05 DOI: 10.22489/CinC.2017.371-097

Jess Tate, Karli Gillette, Brett Burton, Wilson Good, Jaume Coll-Font, Dana Brooks, Rob MacLeod

{"title":"Analyzing Source Sampling to Reduce Error in ECG Forward Simulations.","authors":"Jess Tate, Karli Gillette, Brett Burton, Wilson Good, Jaume Coll-Font, Dana Brooks, Rob MacLeod","doi":"10.22489/CinC.2017.371-097","DOIUrl":"https://doi.org/10.22489/CinC.2017.371-097","url":null,"abstract":"A continuing challenge in validating ECG Imaging is the persistent error in the associated forward problem observed in experimental studies. One possible cause of error is insufficient representation of the cardiac sources, which is often measured from only the ventricular epicardium, ignoring the endocardium and the atria. We hypothesize that measurements that completely cover the heart are required for accurate forward solutions. In this study, we used simulated and measured cardiac potentials to test the effect of different levels of sampling on the forward simulation. We found that omitting source samples on the atria increases the peak RMS error by a mean of 464 μν when compared the the fully sampled cardiac surface. Increasing the sampling on the atria in stages reduced the average error of the forward simulation proportionally to the number of additional samples and revealed some strategies may reduce error with fewer samples, such as adding samples to the AV plane and the atrial roof. Based on these results, we can design a sampling strategy to use in future validation studies.","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":"44 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103632/pdf/nihms934987.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36432569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

AF Classification from a Short Single Lead ECG Recording: the PhysioNet/Computing in Cardiology Challenge 2017. 从短单导联心电图记录中进行心房颤动分类:2017年生理学/心脏病学计算挑战赛。

Computing in cardiology Pub Date : 2017-09-01 Epub Date: 2018-04-05 DOI: 10.22489/CinC.2017.065-469

Gari D Clifford, Chengyu Liu, Benjamin Moody, Li-Wei H Lehman, Ikaro Silva, Qiao Li, A E Johnson, Roger G Mark

{"title":"AF Classification from a Short Single Lead ECG Recording: the PhysioNet/Computing in Cardiology Challenge 2017.","authors":"Gari D Clifford, Chengyu Liu, Benjamin Moody, Li-Wei H Lehman, Ikaro Silva, Qiao Li, A E Johnson, Roger G Mark","doi":"10.22489/CinC.2017.065-469","DOIUrl":"https://doi.org/10.22489/CinC.2017.065-469","url":null,"abstract":"The PhysioNet/Computing in Cardiology (CinC) Challenge 2017 focused on differentiating AF from noise, normal or other rhythms in short term (from 9-61 s) ECG recordings performed by patients. A total of 12,186 ECGs were used: 8,528 in the public training set and 3,658 in the private hidden test set. Due to the high degree of inter-expert disagreement between a significant fraction of the expert labels we implemented a mid-competition bootstrap approach to expert relabeling of the data, levering the best performing Challenge entrants' algorithms to identify contentious labels. A total of 75 independent teams entered the Challenge using a variety of traditional and novel methods, ranging from random forests to a deep learning approach applied to the raw data in the spectral domain. Four teams won the Challenge with an equal high F1 score (averaged across all classes) of 0.83, although the top 11 algorithms scored within 2% of this. A combination of 45 algorithms identified using LASSO achieved an F1 of 0.87, indicating that a voting approach can boost performance.","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":"44 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.22489/CinC.2017.065-469","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36188778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 555

ECG-Based Reconstruction of Heart Position and Orientation with Bayesian Optimization. 基于心电图的心脏位置和方位的贝叶斯优化重建。

Computing in cardiology Pub Date : 2017-09-01 Epub Date: 2018-04-05 DOI: 10.22489/CinC.2017.054-387

Jaume Coll-Font, Setareh Ariafar, Dana H Brooks

{"title":"ECG-Based Reconstruction of Heart Position and Orientation with Bayesian Optimization.","authors":"Jaume Coll-Font, Setareh Ariafar, Dana H Brooks","doi":"10.22489/CinC.2017.054-387","DOIUrl":"https://doi.org/10.22489/CinC.2017.054-387","url":null,"abstract":"Respiratory motion is known to cause beat-to-beat variation of the ECG. This observation suggests that it may be possible to use this variation to track position and orientation of the heart. Electrocardiographic Imaging (ECGI) would benefit from such a reconstruction since one contribution to errors in its solutions is respiratory motion of the heart. ECGI solutions generally rely on prior computation of a \"forward\" model that relates cardiac electrical activity to ECGs. However, the ill-posed nature of the inverse solution leads to large errors in ECGI even for small amounts of error in the forward model. The current work is a first step towards reducing those errors using a nominal forward model and the ECG itself. We describe a method that can reconstruct cardiac position / orientation using known potentials on both the heart and torso. Our current implementation is based on Bayesian Optimization and efficiently optimizes for the position / orientation of the heart to minimize error between measured and forward-computed torso potentials. We evaluated our approach with synthesized torso potentials under a model of respiratory motion and also using potentials recorded in a tank experiment on a canine epicardium and the tank surfaces. Our results show that our method performs accurately in synthetic experiments and can account for part of the error between forward-computed and measured ECGs in the tank experiments.","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":"44 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.22489/CinC.2017.054-387","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36247499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5