Electrocardiogram (ECG) signal quality assessment (SQA) plays a vital role in significantly
improving the diagnostic accuracy and reliability of unsupervised ECG analysis systems. In …

Clinical data management systems typically provide caregiver teams with useful information,
derived from large, sometimes highly heterogeneous, data sources that are often changing …

The identification of the exact positions of the first and second heart sounds within a
phonocardiogram (PCG), or heart sound segmentation, is an essential step in the automatic …

In this paper, we propose a novel signal quality-aware Internet of Things (IoT)-enabled
electrocardiogram (ECG) telemetry system for continuous cardiac health monitoring …

Affect recognition is an interdisciplinary research field bringing together researchers from
natural and social sciences. Affect recognition research aims to detect the affective state of a …

A photoplethysmogram (PPG) is a noninvasive circulatory signal related to the pulsatile
volume of blood in tissue and is typically collected by pulse oximeters. PPG signals collected …

Recently, development of wearable and Internet of Things (IoT) technologies enables the
real-time and continuous individual electrocardiogram (ECG) monitoring. In this paper, we …

Current electrocardiogram (ECG) signal quality assessment studies have aimed to provide a
two-level classification: clean or noisy. However, clinical usage demands more specific …

Objective: Automatic detection and classification of noises can play a vital role in the
development of robust unsupervised electrocardiogram (ECG) analysis systems. This paper …

Electrocardiogram (ECG) signal quality indices (SQIs) are essential for improving diagnostic
accuracy and reliability of ECG analysis systems. In various practical applications, the ECG …