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Effective feature extraction of ECG for biometric application
Biometric systems performing identity recognition based upon extracted informative data
from an individual are vital for security applications. The vital characteristics of an ECG …
from an individual are vital for security applications. The vital characteristics of an ECG …
[HTML][HTML] DCETEN: A lightweight ECG automatic classification network based on Transformer model
F Jiang, J **ao, L Liu, C Wang - Digital Communications and Networks, 2024 - Elsevier
Abstract Currently, Cardiovascular Disease (CVD) remains a significant contributor to
premature mortality and escalating health care expenses. Early and accurate detection is …
premature mortality and escalating health care expenses. Early and accurate detection is …
[PDF][PDF] Feature extraction of electrocardiogram signal using machine learning classification
In the various field of life person identification is an essential and important task. This helps
for the investigation of criminal activities and used in various type of forensic applications …
for the investigation of criminal activities and used in various type of forensic applications …
SoC-Based Implementation of 1-D Convolutional Neural Network for 3-Channel ECG Arrhythmia Classification via HLS4ML
Real-time monitoring of 1-D biopotentials, such as electrocardiograms (ECG), necessitates
effective feature extraction and classification, a strength of deep learning (DL) algorithms …
effective feature extraction and classification, a strength of deep learning (DL) algorithms …
[Retracted] A Multimodel Fusion Method for Cardiovascular Disease Detection Using ECG
G Song, J Zhang, D Mao, G Chen… - Emergency Medicine …, 2022 - Wiley Online Library
Objective. Electrocardiogram (ECG) is an important diagnostic tool that has been the subject
of much research in recent years. Owing to a lack of well‐labeled ECG record databases …
of much research in recent years. Owing to a lack of well‐labeled ECG record databases …
DIFDD: Deep intelligence framework for disease detection using patients electrocardiogram signals and X-ray images
Heart disease has been the leading cause of mortality worldwide in the recent decade.
Since 2019, new lung-related infections have increased heart attack mortality. To minimize …
Since 2019, new lung-related infections have increased heart attack mortality. To minimize …
[PDF][PDF] Stationary wavelet transform and entropy-based features for ECG beat classification
In this study, heartbeats are classified as normal, right bundle branch block (Rbbb), paced
beat, and left bundle branch block (Lbbb), using the electrocardiography (ECG) signals from …
beat, and left bundle branch block (Lbbb), using the electrocardiography (ECG) signals from …
Alerting system for sport activity based on ECG signals using proportional integral derivative
Exercise makes the body fit, but most people do not know the intensity of the exercise they
are doing right or otherwise can be dangerous, because not everyone knows the maximum …
are doing right or otherwise can be dangerous, because not everyone knows the maximum …
Automatic Diagnosis of Cardiovascular Diseases from ECG Signals using Convolutional Neural Network and Soft Computing Methods
S Goyal - 2022 - researchsquare.com
Since the last decade, the Electrocardiogram (ECG) tool has received medical experts and
researchers' attention for accurate and fast diagnosis of cardiovascular diseases (CVD). The …
researchers' attention for accurate and fast diagnosis of cardiovascular diseases (CVD). The …
Arrhythmia discrimination using support vector machine
In this paper support vector machine (SVM) classifier is developed for the classification of
two types of arrhythmias ie premature ventricular contraction (PVC) and atrial premature …
two types of arrhythmias ie premature ventricular contraction (PVC) and atrial premature …