A review on computational methods for denoising and detecting ECG signals to detect cardiovascular diseases
Cardiac health of the human heart is an intriguing issue for many decades as cardiovascular
diseases (CVDs) are the leading cause of death worldwide. Electrocardiogram (ECG) signal …
diseases (CVDs) are the leading cause of death worldwide. Electrocardiogram (ECG) signal …
From ECG signals to images: a transformation based approach for deep learning
Provocative heart disease is related to ventricular arrhythmias (VA). Ventricular
tachyarrhythmia is an irregular and fast heart rhythm that emerges from inappropriate …
tachyarrhythmia is an irregular and fast heart rhythm that emerges from inappropriate …
Detection of R-peaks using fractional Fourier transform and principal component analysis
An electrocardiogram (ECG) is world's most recognized, widely accepted and essential
primitive diagnostic tool to assess health status of heart of a subject (patient) by analyzing its …
primitive diagnostic tool to assess health status of heart of a subject (patient) by analyzing its …
Wavelet transform and vector machines as emerging tools for computational medicine
V Gupta - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Electrocardiogram (ECG) is a most primitive and important test to analyse the status of the
heart functioning. During this test, different types of noises and artefacts get involved in the …
heart functioning. During this test, different types of noises and artefacts get involved in the …
A comprehensive review of computer-based Techniques for R-peaks/QRS complex detection in ECG signal
Electrocardiogram (ECG) signal, which is composite of multiple segments such as P-wave,
QRS complex and T-wave, plays a crucial role in the treatment of cardiovascular disease …
QRS complex and T-wave, plays a crucial role in the treatment of cardiovascular disease …
A novel FrWT based arrhythmia detection in ECG signal using YWARA and PCA
In general, Electrocardiogram (ECG) signal gets corrupted by variety of noise at the time of
its acquisition. Unfortunately, these noise tend to mask the crucial information …
its acquisition. Unfortunately, these noise tend to mask the crucial information …
QRS complex detection using novel deep learning neural networks
W Cai, D Hu - IEEE Access, 2020 - ieeexplore.ieee.org
Objective: Accurate QRS complex detection is essential for electrocardiography (ECG)
diagnosis. Many proposed algorithms don't perform satisfactorily on noisy and arrhythmia …
diagnosis. Many proposed algorithms don't perform satisfactorily on noisy and arrhythmia …
PCA as an effective tool for the detection of R-peaks in an ECG signal processing
Visual inspection of R-peaks in Electrocardiogram (ECG) signal is avoided because of
limited resolution and in the variation of parameters of the underlying subject (patient) …
limited resolution and in the variation of parameters of the underlying subject (patient) …
Arrhythmia detection in ECG signal using fractional wavelet transform with principal component analysis
Any significant alteration in the Electro-Cardio-Gram (ECG) signal wave components (P-
QRS-T) for a time duration is detected as arrhythmia. In this paper, a novel fractional wavelet …
QRS-T) for a time duration is detected as arrhythmia. In this paper, a novel fractional wavelet …
An improved cardiac arrhythmia classification using an RR interval-based approach
Accurate and early detection of cardiac arrhythmia present in an electrocardiogram (ECG)
can prevent many premature deaths. Cardiac arrhythmia arises due to the improper …
can prevent many premature deaths. Cardiac arrhythmia arises due to the improper …