Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …

Bioadhesive devices can be used to create conformable tissue–device interfaces without
suturing. However, the development of such technology faces challenges related to the …

Deep learning has made many advances in data classification using electrocardiogram
(ECG) waveforms. Over the past decade, data science research has focused on develo** …

A preliminary study into the signal quality of the Empatica's E4 portable
photoplethysmogram device as validation for further research on using the device to detect …

Deep learning models developed through multi-lead electrocardiogram (ECG) signals are
considered the leading methods for the automated detection of arrhythmia on computer …

Accurate and early detection of cardiac arrhythmia present in an electrocardiogram (ECG)
can prevent many premature deaths. Cardiac arrhythmia arises due to the improper …

Accurate automated detection of P waves in ECG allows to provide fast correct diagnosis of
various cardiac arrhythmias and select suitable strategy for patients' treatment. However, P …

Background: Electrographic interpretation skills are important for healthcare practitioners
caring for patients in need of cardiac assessment. Competency in ECG interpretation skills is …

Over the last decade, deep learning applications in biomedical research have exploded,
demonstrating their ability to often outperform previous machine learning approaches in …

Accurate detection of key components in an electrocardiogram (ECG) plays a vital role in
identifying cardiovascular diseases. In this work, we proposed a novel and lightweight P …