IJERPH, Vol. 16, Pages 4068: Hypertension Diagnosis Index for Discrimination of High-Risk Hypertension ECG Signals Using Optimal Orthogonal Wavelet Filter Bank

IJERPH, Vol. 16, Pages 4068: Hypertension Diagnosis Index for Discrimination of High-Risk Hypertension ECG Signals Using Optimal Orthogonal Wavelet Filter Bank International Journal of Environmental Research and Public Health doi: 10.3390/ijerph16214068 Authors: Jaypal Singh Rajput Manish Sharma U. Rajendra Acharya Hypertension (HT) is an extreme increment in blood pressure that can prompt a stroke, kidney disease, and heart attack. HT does not show any symptoms at the early stage, but can lead to various cardiovascular diseases. Hence, it is essential to identify it at the beginning stages. It is tedious to analyze electrocardiogram (ECG) signals visually due to their low amplitude and small bandwidth. Hence, to avoid possible human errors in the diagnosis of HT patients, an automated ECG-based system is developed. This paper proposes the computerized segregation of low-risk hypertension (LRHT) and high-risk hypertension (HRHT) using ECG signals with an optimal orthogonal wavelet filter bank (OWFB) system. The HRHT class is comprised of patients with myocardial infarction, stroke, and syncope ECG signals. The ECG-data are acquired from physionet’s smart health for accessing risk via ECG event (SHAREE) database, which contains recordings of a total 139 subjects. First, ECG signals are segmented into epochs of 5 min. The segmented epochs are then decomposed into six wavelet sub-bands (WSBs) using OWFB. We extract the signal fractional dimension (SFD) ...
Source: International Journal of Environmental Research and Public Health - Category: Environmental Health Authors: Tags: Article Source Type: research