Electrocardiogram Comparison as a Biometric Identifier: A Review

A Kadi, A Oubelaid, SK Towfek - Full Length Article, 2023 - americaspg.com
The electrocardiogram (ECG) is a type of biometric data that has recently attracted a lot of
attention as a potentially useful biometric trait due to its high discriminatory power. However …

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 …

Lossy image compression with compressive autoencoders

L Theis, W Shi, A Cunningham, F Huszár - arxiv preprint arxiv:1703.00395, 2017 - arxiv.org
We propose a new approach to the problem of optimizing autoencoders for lossy image
compression. New media formats, changing hardware technology, as well as diverse …

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines

D Charte, F Charte, S García, MJ del Jesus, F Herrera - Information Fusion, 2018 - Elsevier
Many of the existing machine learning algorithms, both supervised and unsupervised,
depend on the quality of the input characteristics to generate a good model. The amount of …

An efficient compression of ECG signals using deep convolutional autoencoders

O Yildirim, R San Tan, UR Acharya - Cognitive Systems Research, 2018 - Elsevier
Background and objective Advances in information technology have facilitated the retrieval
and processing of biomedical data. Especially with wearable technologies and mobile …

Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types

SL Oh, EYK Ng, R San Tan, UR Acharya - Computers in biology and …, 2019 - Elsevier
Abnormality of the cardiac conduction system can induce arrhythmia―abnormal heart
rhythm―that can frequently lead to other cardiac diseases and complications, and are …

High-ratio lossy compression: Exploring the autoencoder to compress scientific data

T Liu, J Wang, Q Liu, S Alibhai, T Lu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Scientific simulations on high-performance computing (HPC) systems can generate large
amounts of floating-point data per run. To mitigate the data storage bottleneck and lower the …

Physics-informed deep learning for signal compression and reconstruction of big data in industrial condition monitoring

M Russell, P Wang - Mechanical Systems and Signal Processing, 2022 - Elsevier
The onset of the Internet of Things enables machines to be outfitted with always-on sensors
that can provide health information to cloud-based monitoring systems for prognostics and …

A novel dimensionality reduction approach for ECG signal via convolutional denoising autoencoder with LSTM

E Dasan, I Panneerselvam - Biomedical Signal Processing and Control, 2021 - Elsevier
Typical IoT based e-health scenarios use resource constrained wearable device to facilitate
ubiquitous long-term monitoring for chronic conditions like cardiovascular disease (CVD) …

A deep learning technique for biometric authentication using ECG beat template matching

AJ Prakash, KK Patro, S Samantray, P Pławiak… - Information, 2023 - mdpi.com
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 …