Accurate automated detection of congestive heart failure using eigenvalue decomposition based features extracted from HRV signals

• Autorzy: Sharma Rishi Raj , Kumar Ashish , Pachori Ram Bilas , Acharya U. Rajendra

Identyfikatory

DOI

10.1016/j.bbe.2018.10.001

• Języki publikacji: EN

Abstrakty

EN

Congestive heart failure (CHF) is a cardiac abnormality in which heart is not able to pump sufficient blood to meet the requirement of all the parts of the body. This study aims to diagnose the CHF accurately using heart rate variability (HRV) signals. The HRV signals are non-stationary and nonlinear in nature. We have used eigenvalue decomposition of Hankel matrix (EVDHM) method to analyze the HRV signals. The lowest frequency component (LFC) and the highest frequency component (HFC) are extracted from the eigenvalue decomposed components of HRV signals. After that, the mean and standard deviation in time domain, mean frequency calculated from Fourier-Bessel series expansion, k-nearest neighbor (k-NN) entropy, and correntropy features are evaluated from the decomposed components. The ranked features based on t-value are fed to least-squares support vector machine (LS-SVM) classifier with radial basis function (RBF) kernel for automated diagnosis of CHF HRV signals. The study is performed on three normal datasets and two CHF datasets. Our proposed system has yielded an accuracy of 93.33%, sensitivity of 91.41%, and specificity of 94.90% using 500 HRV samples. The automated toolkit can aid cardiac physicians in the accurate diagnosis of CHF patients to confirm their findings with our system. Hence, it will help to provide timely treatment for CHF patients and save life.

Słowa kluczowe

EN

eigenvalue decomposition; Hankel matrix; congestive heart failure; heart rate variability; non-stationary signal analysis

PL

macierz Hankela; zastoinowa niewydolność serca; zmienność rytmu zatokowego; analiza sygnałów niestacjonarnych

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2019
• Tom: Vol. 39, no. 2
• Strony: 312--327
• Opis fizyczny: Bibliogr. 83 poz., rys., tab., wykr.

Twórcy

autor

Sharma Rishi Raj

• Discipline of Electrical Engineering, Indian Institute of Technology Indore, Indore 453552, India

autor

Kumar Ashish

• Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, India

autor

Pachori Ram Bilas

• Discipline of Electrical Engineering, Indian Institute of Technology Indore, Indore, India

autor

Acharya U. Rajendra

• Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore, Singapore; Department of Biomedical Engineering, School of Science and Technology, SUSS, Singapore, Singapore; Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Malaysia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).