EEG based interpretation of human brain activity during yoga and meditation using machine learning: A systematic review
Objectives The present investigation is to study the impact of yoga and meditation on Brain
waves concerning physical and mental health. There are mainly three stages (steps) in the …
waves concerning physical and mental health. There are mainly three stages (steps) in the …
Artificial intelligence methods for analysis of electrocardiogram signals for cardiac abnormalities: state-of-the-art and future challenges
SK Saini, R Gupta - Artificial Intelligence Review, 2022 - Springer
Abstract Cardiovascular diseases (CVDs) in India and globally are the major cause of
mortality, as revealed by the World Health Organization (WHO). The irregularities in the pace …
mortality, as revealed by the World Health Organization (WHO). The irregularities in the pace …
Efficient prediction of cardiovascular disease using machine learning algorithms with relief and LASSO feature selection techniques
Cardiovascular diseases (CVD) are among the most common serious illnesses affecting
human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce …
human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce …
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
This article presents a new deep learning approach for cardiac arrhythmia (17 classes)
detection based on long-duration electrocardiography (ECG) signal analysis …
detection based on long-duration electrocardiography (ECG) signal analysis …
[PDF][PDF] Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
P Pławiak, UR Acharya - Neural Comput. Appl, 2020 - researchgate.net
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …
million persons have cardiovascular diseases around the world. Our proposed work based …
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 …
Novel genetic ensembles of classifiers applied to myocardium dysfunction recognition based on ECG signals
P Pławiak - Swarm and evolutionary computation, 2018 - Elsevier
This article presents an innovative genetic ensembles of classifiers applied to classification
of cardiac disorders (17 classes) based on electrocardiography (ECG) signal analysis. From …
of cardiac disorders (17 classes) based on electrocardiography (ECG) signal analysis. From …
ECG recurrence plot-based arrhythmia classification using two-dimensional deep residual CNN features
In this paper, an effective electrocardiogram (ECG) recurrence plot (RP)-based arrhythmia
classification algorithm that can be implemented in portable devices is presented. Public …
classification algorithm that can be implemented in portable devices is presented. Public …
Atrial fibrillation detection based on multi-feature extraction and convolutional neural network for processing ECG signals
X Chen, Z Cheng, S Wang, G Lu, G Xv, Q Liu… - Computer Methods and …, 2021 - Elsevier
Background and objective The incidence of atrial fibrillation is increasing annually. We
develop an automatic detection system, which is of great significance for the early detection …
develop an automatic detection system, which is of great significance for the early detection …
Novel DERMA fusion technique for ECG heartbeat classification
An electrocardiogram (ECG) consists of five types of different waveforms or characteristics
(P, QRS, and T) that represent electrical activity within the heart. Identification of time …
(P, QRS, and T) that represent electrical activity within the heart. Identification of time …