A deep learning approach for ECG-based heartbeat classification for arrhythmia detection
G Sannino, G De Pietro - Future Generation Computer Systems, 2018 - Elsevier
Classification is one of the most popular topics in healthcare and bioinformatics, especially
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
Advances of ecg sensors from hardware, software and format interoperability perspectives
It is well-known that cardiovascular disease is one of the major causes of death worldwide
nowadays. Electrocardiogram (ECG) sensor is one of the tools commonly used by …
nowadays. Electrocardiogram (ECG) sensor is one of the tools commonly used by …
An intelligent health monitoring and diagnosis system based on the internet of things and fuzzy logic for cardiac arrhythmia COVID-19 patients
Background: During the COVID-19 pandemic, there is a global demand for intelligent health
surveillance and diagnosis systems for patients with critical conditions, particularly those …
surveillance and diagnosis systems for patients with critical conditions, particularly those …
The principles of software QRS detection
BU Kohler, C Hennig… - IEEE Engineering in …, 2002 - ieeexplore.ieee.org
The QRS complex is the most striking waveform within the electrocardiogram (ECG). Since it
reflects the electrical activity within the heart during the ventricular contraction, the time of its …
reflects the electrical activity within the heart during the ventricular contraction, the time of its …
Clustering ECG complexes using Hermite functions and self-organizing maps
M Lagerholm, C Peterson, G Braccini… - IEEE Transactions …, 2000 - ieeexplore.ieee.org
An integrated method for clustering of QRS complexes is presented which includes basis
function representation and self-organizing neural networks (NN's). Each QRS complex is …
function representation and self-organizing neural networks (NN's). Each QRS complex is …
Comparative study of morphological and time-frequency ECG descriptors for heartbeat classification
The prompt and adequate detection of abnormal cardiac conditions by computer-assisted
long-term monitoring systems depends greatly on the reliability of the implemented ECG …
long-term monitoring systems depends greatly on the reliability of the implemented ECG …
Feature extraction from ECG signals using wavelet transforms for disease diagnostics
This paper deals with a modified combined wavelet transform technique that has been
developed to analyse multilead electrocardiogram signals for cardiac disease diagnostics …
developed to analyse multilead electrocardiogram signals for cardiac disease diagnostics …
Cardiac arrhythmia diagnosis method using linear discriminant analysis on ECG signals
YC Yeh, WJ Wang, CW Chiou - Measurement, 2009 - Elsevier
This work describes a Linear Discriminant Analysis (LDA) method to analyze ECG signals
for diagnosing cardiac arrhythmias effectively. The proposed method can accurately classify …
for diagnosing cardiac arrhythmias effectively. The proposed method can accurately classify …
Distinct ECG phenotypes identified in hypertrophic cardiomyopathy using machine learning associate with arrhythmic risk markers
Aims: Ventricular arrhythmia triggers sudden cardiac death (SCD) in hypertrophic
cardiomyopathy (HCM), yet electrophysiological biomarkers are not used for risk …
cardiomyopathy (HCM), yet electrophysiological biomarkers are not used for risk …
Total removal of baseline drift from ECG signal
VS Chouhan, SS Mehta - 2007 International Conference on …, 2007 - ieeexplore.ieee.org
Baseline drift in ECG signal is the biggest hurdle in visualization of correct waveform and
computerized detection of wave complexes based on threshold decision. The baseline drift …
computerized detection of wave complexes based on threshold decision. The baseline drift …