Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review
Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …
tools in medicine and healthcare. Deep learning methods have achieved promising results …
A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
AN Uwaechia, DA Ramli - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …
and has recently received significant interest as a promising biometric trait. However, ECG …
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 …
BAED: A secured biometric authentication system using ECG signal based on deep learning techniques
Biometric authentication technology has become increasingly common in our daily lives as
information protection and control regulation requirements have grown worldwide. A …
information protection and control regulation requirements have grown worldwide. A …
Generative adversarial network with transformer generator for boosting ECG classification
Y Xia, Y Xu, P Chen, J Zhang, Y Zhang - Biomedical Signal Processing and …, 2023 - Elsevier
Arrhythmia is an important group of cardiovascular diseases, which can suddenly attack and
cause sudden death, or continue to affect the heart and cause its failure. Electrocardiogram …
cause sudden death, or continue to affect the heart and cause its failure. Electrocardiogram …
Ecg biometric authentication: A comparative analysis
Robust authentication and identification methods become an indispensable urgent task to
protect the integrity of the devices and the sensitive data. Passwords have provided access …
protect the integrity of the devices and the sensitive data. Passwords have provided access …
PerAE: an effective personalized AutoEncoder for ECG-based biometric in augmented reality system
L Sun, Z Zhong, Z Qu, N Xiong - IEEE journal of biomedical and …, 2022 - ieeexplore.ieee.org
With the development of the Augmented and Virtual Reality (AR/VR) technologies, massive
biometric data are collected by different organizations. These data have great significance …
biometric data are collected by different organizations. These data have great significance …
Using convolutional neural network and a single heartbeat for ECG biometric recognition
DA AlDuwaile, MS Islam - Entropy, 2021 - mdpi.com
The electrocardiogram (ECG) signal has become a popular biometric modality due to
characteristics that make it suitable for developing reliable authentication systems. However …
characteristics that make it suitable for developing reliable authentication systems. However …
A deep learning technique for biometric authentication using ECG beat template matching
An electrocardiogram (ECG) is a unique representation of a person's identity, similar to
fingerprints, and its rhythm and shape are completely different from person to person …
fingerprints, and its rhythm and shape are completely different from person to person …
A novel continuous authentication method using biometrics for IOT devices
DR Bhuva, S Kumar - Internet of Things, 2023 - Elsevier
In this paper, we examine continuous authentication for IoT devices using real-time
biometrics of a person's electrocardiogram (ECG) and electromyography (EMG). ECG is …
biometrics of a person's electrocardiogram (ECG) and electromyography (EMG). ECG is …