Heat map visualization for electrocardiogram data analysis
Abstract Background Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. Few papers display ECG data by visual means. The aim of this study was to analyze and show data for electrocardi...
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doaj-69318eadebf347519b72cae5d2851ffd2020-11-25T01:59:21ZengBMCBMC Cardiovascular Disorders1471-22612020-06-012011810.1186/s12872-020-01560-8Heat map visualization for electrocardiogram data analysisHaisen Guo0Weidai Zhang1Chumin Ni2Zhixiong Cai3Songming Chen4Xiansheng Huang5Department of Cardiology, Shantou Central HospitalDepartment of Cardiology, Shantou Central HospitalDepartment of Cardiology, Shantou Central HospitalDepartment of Cardiology, Shantou Central HospitalDepartment of Cardiology, the First Affiliated Hospital of Shantou University Medical CollegeDepartment of Cardiology, the First Affiliated Hospital of Shantou University Medical CollegeAbstract Background Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. Few papers display ECG data by visual means. The aim of this study was to analyze and show data for electrocardiographic left ventricular hypertrophy (LVH) with ST-segment elevation (STE) by a heat map in order to explore the feasibility and clinical value of heat mapping for ECG data visualization. Methods We sequentially collected the electrocardiograms of inpatients in the First Affiliated Hospital of Shantou University Medical College from July 2015 to December 2015 in order to screen cases of LVH with STE. HemI 1.0 software was used to draw heat maps to display the STE of each lead of each collected ECG. Cluster analysis was carried out based on the heat map and the results were drawn as tree maps (pedigree maps) in the heat map. Results In total, 60 cases of electrocardiographic LVH with STE were screened and analyzed. STE leads were mainly in the V1, V2 and V3 leads. The ST-segment shifts of each lead of each collected ECG could be conveniently visualized in the heat map. According to cluster analysis in the heat map, STE leads were clustered into two categories, comprising of the right precordial leads (V1, V2, V3) and others (V4, V5, V6, I, II, III, aVF, aVL, aVR). Moreover, the STE amplitude in 40% (24 out of 60) of cases reached the threshold specified in the STEMI guideline. These cases also could be fully displayed and visualized in the heat map. Cluster analysis in the heat map showed that the III, aVF and aVR leads could be clustered together, the V1, V2, V3 and V4 leads could be clustered together, and the V5, V6, I and aVL leads could be clustered together. Conclusion Heat maps and cluster analysis can be used to fully display every lead of each electrocardiogram and provide relatively comprehensive information.http://link.springer.com/article/10.1186/s12872-020-01560-8Heat mapVisualizationElectrocardiogramData analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Haisen Guo Weidai Zhang Chumin Ni Zhixiong Cai Songming Chen Xiansheng Huang |
spellingShingle |
Haisen Guo Weidai Zhang Chumin Ni Zhixiong Cai Songming Chen Xiansheng Huang Heat map visualization for electrocardiogram data analysis BMC Cardiovascular Disorders Heat map Visualization Electrocardiogram Data analysis |
author_facet |
Haisen Guo Weidai Zhang Chumin Ni Zhixiong Cai Songming Chen Xiansheng Huang |
author_sort |
Haisen Guo |
title |
Heat map visualization for electrocardiogram data analysis |
title_short |
Heat map visualization for electrocardiogram data analysis |
title_full |
Heat map visualization for electrocardiogram data analysis |
title_fullStr |
Heat map visualization for electrocardiogram data analysis |
title_full_unstemmed |
Heat map visualization for electrocardiogram data analysis |
title_sort |
heat map visualization for electrocardiogram data analysis |
publisher |
BMC |
series |
BMC Cardiovascular Disorders |
issn |
1471-2261 |
publishDate |
2020-06-01 |
description |
Abstract Background Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. Few papers display ECG data by visual means. The aim of this study was to analyze and show data for electrocardiographic left ventricular hypertrophy (LVH) with ST-segment elevation (STE) by a heat map in order to explore the feasibility and clinical value of heat mapping for ECG data visualization. Methods We sequentially collected the electrocardiograms of inpatients in the First Affiliated Hospital of Shantou University Medical College from July 2015 to December 2015 in order to screen cases of LVH with STE. HemI 1.0 software was used to draw heat maps to display the STE of each lead of each collected ECG. Cluster analysis was carried out based on the heat map and the results were drawn as tree maps (pedigree maps) in the heat map. Results In total, 60 cases of electrocardiographic LVH with STE were screened and analyzed. STE leads were mainly in the V1, V2 and V3 leads. The ST-segment shifts of each lead of each collected ECG could be conveniently visualized in the heat map. According to cluster analysis in the heat map, STE leads were clustered into two categories, comprising of the right precordial leads (V1, V2, V3) and others (V4, V5, V6, I, II, III, aVF, aVL, aVR). Moreover, the STE amplitude in 40% (24 out of 60) of cases reached the threshold specified in the STEMI guideline. These cases also could be fully displayed and visualized in the heat map. Cluster analysis in the heat map showed that the III, aVF and aVR leads could be clustered together, the V1, V2, V3 and V4 leads could be clustered together, and the V5, V6, I and aVL leads could be clustered together. Conclusion Heat maps and cluster analysis can be used to fully display every lead of each electrocardiogram and provide relatively comprehensive information. |
topic |
Heat map Visualization Electrocardiogram Data analysis |
url |
http://link.springer.com/article/10.1186/s12872-020-01560-8 |
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