Intelligence in the Internet of Medical Things era: A systematic review of current and future trends
Abstract Internet of Medical Things (IoMT) envisions a network of medical devices and
people, which use wireless communication to enable the exchange of healthcare data …
people, which use wireless communication to enable the exchange of healthcare data …
[HTML][HTML] Analysis of various techniques for ECG signal in healthcare, past, present, and future
Cardiovascular diseases are the primary reason for mortality worldwide. As per WHO survey
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
ECG arrhythmia classification using STFT-based spectrogram and convolutional neural network
J Huang, B Chen, B Yao, W He - IEEE access, 2019 - ieeexplore.ieee.org
The classification of electrocardiogram (ECG) signals is very important for the automatic
diagnosis of heart disease. Traditionally, it is divided into two steps, including the step of …
diagnosis of heart disease. Traditionally, it is divided into two steps, including the step of …
A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification
Ö Yildirim - Computers in biology and medicine, 2018 - Elsevier
Long-short term memory networks (LSTMs), which have recently emerged in sequential data
analysis, are the most widely used type of recurrent neural networks (RNNs) architecture …
analysis, are the most widely used type of recurrent neural networks (RNNs) architecture …
[HTML][HTML] ECG-based heartbeat classification for arrhythmia detection: A survey
An electrocardiogram (ECG) measures the electric activity of the heart and has been widely
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
ECG classification using wavelet packet entropy and random forests
T Li, M Zhou - Entropy, 2016 - mdpi.com
The electrocardiogram (ECG) is one of the most important techniques for heart disease
diagnosis. Many traditional methodologies of feature extraction and classification have been …
diagnosis. Many traditional methodologies of feature extraction and classification have been …
Classification of arrhythmia by using deep learning with 2-D ECG spectral image representation
The electrocardiogram (ECG) is one of the most extensively employed signals used in the
diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture …
diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture …
Classification of ECG arrhythmia using recurrent neural networks
Abstract In this paper, Recurrent Neural Networks (RNN) have been applied for classifying
the normal and abnormal beats in an ECG. The primary aim of this paper was to enable …
the normal and abnormal beats in an ECG. The primary aim of this paper was to enable …
A hybrid deep CNN model for abnormal arrhythmia detection based on cardiac ECG signal
Electrocardiogram (ECG) signals play a vital role in diagnosing and monitoring patients
suffering from various cardiovascular diseases (CVDs). This research aims to develop a …
suffering from various cardiovascular diseases (CVDs). This research aims to develop a …
Novel methodology of cardiac health recognition based on ECG signals and evolutionary-neural system
P Pławiak - Expert Systems with Applications, 2018 - Elsevier
This article presents an innovative research methodology that enables the efficient
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …