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 …

Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

Electrocardiogram (ECG) recordings are indicative for the state of the human heart.
Automatic analysis of these recordings can be performed using various computational …

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 …

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 …

Electrocardiography (ECG) is widely used for arrhythmia detection nowadays. The machine
learning methods with signal processing algorithms have been used for automated …

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 …

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 …

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 …

Face and fingerprint are, currently, the most thoroughly explored biometric traits, promising
reliable recognition in diverse applications. Commercial products using these traits for …