DocumentCode :
3596911
Title :
Clinical characterization by Principal Component Analysis of stress test ECG
Author :
Bortolan, Giovanni ; Christov, Ivaylo ; Simova, Iana ; Dimitrov, N. ; Jekova, Irena ; Krasteva, Vessela
Author_Institution :
Inst. of Biomed. Eng. (ISIB), Padua, Italy
fYear :
2012
Firstpage :
613
Lastpage :
616
Abstract :
The aim of the study is to investigate whether and how QRS-complex and T-wave heterogeneity is influenced by different cardiac risk factors and clinical data. Digital ECG during stress test was acquired in 106 patients (age 63±10 years, 45 males). Two indices obtained by Principal Component Analysis (PCA): complexity (PCA1) and non-linear components (PCA2) were used for the analysis of the heterogeneity of the different clinical groups. Mean, max, and standard deviation values were examined in the study. Significant difference (p<;0.01÷0.05) between PCA1 of QRS (PCA1_QRS) was found between subgroups of patients defined according to the presence or absence of angina pectoris, diabetes mellitus, stroke and smokers. Significant difference for PCA2_QRS was obtained in the presence of angiographically significant coronary artery disease, diabetes mellitus, positive stress test and triglycerides. For the T wave significant difference was found respectively for PCA1_T in: myocardial infarction, angiographically significant coronary artery disease and gender and for PCA2_T in: angiographically significant coronary artery disease, percutaneous coronary intervention and gender.
Keywords :
diseases; electrocardiography; medical signal processing; principal component analysis; PCA; QRS-complex heterogeneity; T-wave heterogeneity; angina pectoris; angiographically significant coronary artery disease; cardiac risk factors; clinical characterization; clinical data; diabetes mellitus; gender; max deviation values; mean deviation values; myocardial infarction; nonlinear components; percutaneous coronary intervention; principal component analysis; smokers; standard deviation values; stress test ECG; stroke; triglycerides; Arteries; Complexity theory; Design automation; Diseases; Electrocardiography; Principal component analysis; Stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing in Cardiology (CinC), 2012
ISSN :
2325-8861
Print_ISBN :
978-1-4673-2076-4
Type :
conf
Filename :
6420468
Link To Document :
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