The current state-of-the-art in automatic QRS detection methods show high robustness and
almost negligible error rates. In return, the methods are usually based on machine-learning …

A large part of the biomedical research spectrum is dedicated to develop electrocardiogram
(ECG) signal processing techniques to contribute to early diagnosis. However, it is common …

A low-power long-term ambulatory ECG monitor was developed for the acquisition, storage
and processing of three simultaneous leads DI, aVF and V2 with a beat-to-beat heart rate …

Accurate detection of characteristic electrocardiogram (ECG) waves is necessary for ECG
analysis and interpretation. In this paper, we distinguish four processing steps of detection …

This work describes an algorithm intended to detect the beat-to-beat heart rate from the
ballistocardiogram (BCG) obtained from seated subjects. The algorithm is based on the …

A reversible watermarking algorithm with high data-hiding capacity has been developed for
electrocardiogram (ECG) signal based on wavelet transforms. In electrocardiogram signal …

Cardiovascular diseases are currently the leading cause of death worldwide. Thus, there is
a need for non-invasive ambulatory (Holter) ECG monitors with automatic measurements of …

Objective The present study aims to simulate an alarm system for online detecting normal
electrocardiogram (ECG) signals from abnormal ECG so that an individual's heart condition …

With the advancement of the Internet of Medical Things technology, many vital sign-sensing
devices are being developed. Among the diverse healthcare devices, portable …

Electrocardiogram (ECG) signals are composed of five important waves: P, Q, R, S, and T.
Sometimes, a sixth wave (U) may follow T. Q, R, and S are grouped together to form the QRS …