[HTML][HTML] A review on deep learning methods for ECG arrhythmia classification
Z Ebrahimi, M Loni, M Daneshtalab… - Expert Systems with …, 2020 - Elsevier
Deep Learning (DL) has recently become a topic of study in different applications including
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
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 …
[HTML][HTML] Comprehensive survey of computational ECG analysis: Databases, methods and applications
E Merdjanovska, A Rashkovska - Expert Systems with Applications, 2022 - Elsevier
Electrocardiogram (ECG) recordings are indicative for the state of the human heart.
Automatic analysis of these recordings can be performed using various computational …
Automatic analysis of these recordings can be performed using various computational …
A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities
Biometrics is the branch of science that deals with the identification and verification of an
individual based on the physiological and behavioral traits. These traits or identifiers are …
individual based on the physiological and behavioral traits. These traits or identifiers are …
An efficient ECG arrhythmia classification method based on Manta ray foraging optimization
The Electrocardiogram (ECG) arrhythmia classification has become an interesting research
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals
Electrocardiography (ECG) is widely used for arrhythmia detection nowadays. The machine
learning methods with signal processing algorithms have been used for automated …
learning methods with signal processing algorithms have been used for automated …
Multimodal biometric authentication systems using convolution neural network based on different level fusion of ECG and fingerprint
A multimodal biometric system integrates information from more than one biometric modality
to improve the performance of each individual biometric system and make the system robust …
to improve the performance of each individual biometric system and make the system robust …
[PDF][PDF] Arrhythmia modern classification techniques: A review
M Saber, M Abotaleb - J. Artif. Intell. Metaheuristics, 2022 - researchgate.net
Artificial intelligence methods are utilized in biological signal processing to locate and
extract interesting data. The examination of ECG signal characteristics is crucial for the …
extract interesting data. The examination of ECG signal characteristics is crucial for the …
[HTML][HTML] Soft electronics for health monitoring assisted by machine learning
Due to the development of the novel materials, the past two decades have witnessed the
rapid advances of soft electronics. The soft electronics have huge potential in the physical …
rapid advances of soft electronics. The soft electronics have huge potential in the physical …
Evolution, current challenges, and future possibilities in ECG biometrics
Face and fingerprint are, currently, the most thoroughly explored biometric traits, promising
reliable recognition in diverse applications. Commercial products using these traits for …
reliable recognition in diverse applications. Commercial products using these traits for …