A critical review of feature extraction techniques for ECG signal analysis
An Electrocardiogram (ECG) is a primary and most prevalent non-invasive test performed on
the subjects'(ie patients') with suspected heart problems. It helps in diagnosing important …
the subjects'(ie patients') with suspected heart problems. It helps in diagnosing important …
Hybrid CNN-LSTM deep learning model and ensemble technique for automatic detection of myocardial infarction using big ECG data
HM Rai, K Chatterjee - Applied Intelligence, 2022 - Springer
Automatic and accurate prognosis of myocardial infarction (MI) using electrocardiogram
(ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is …
(ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is …
A review of different ECG classification/detection techniques for improved medical applications
Electrocardiogram (ECG) is an important diagnostic tool in medical engineering, presented
in the form of electrical signal. Its complete analysis requires three stages viz. pre …
in the form of electrical signal. Its complete analysis requires three stages viz. pre …
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 …
An efficient AR modelling-based electrocardiogram signal analysis for health informatics
Today, health informatics not only requires correct but also timely diagnosis much before the
occurrence of critical stage of the underlying disease. Electrocardiogram (ECG) is one such …
occurrence of critical stage of the underlying disease. Electrocardiogram (ECG) is one such …
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 …
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 …
ECG signal analysis using CWT, spectrogram and autoregressive technique
The cardiovascular system is a combination of the heart, blood and blood vessels.
Cardiovascular diseases (CVD) are a key factor behind casualties worldwide among both …
Cardiovascular diseases (CVD) are a key factor behind casualties worldwide among both …
Evaluation of handcrafted features and learned representations for the classification of arrhythmia and congestive heart failure in ECG
Electrocardiogram (ECG) is considered as an essential diagnostic tool to investigate life-
threatening cardiac abnormalities, such as arrhythmia and congestive heart failure. It is …
threatening cardiac abnormalities, such as arrhythmia and congestive heart failure. It is …