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

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

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

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

By considering limited resource-constraints of medical devices and advanced deep learning
networks, in this paper, we explore a lightweight convolutional neural network (CNN) based …

The degraded quality of the electrocardiogram (ECG) signals is the main source of false
alarms in critical care units. Therefore, a preliminary analysis of the ECG signal is required to …

In this Letter, a robust technique is presented to detect and classify different
electrocardiogram (ECG) noises including baseline wander (BW), muscle artefact (MA) …

Removalof ocular artifacts (OAs) from electroencephalogram (EEG) signal is crucial for
accurate and effective EEG analysis and brain-computer interface research. The elimination …

In this paper, the authors present an automated method for quality assessment of
electrocardiogram (ECG) signal. Our proposed method not only detects and classifies the …

In this paper, we present a straightforward automatic QRS complex detection method for
electrocardiogram (ECG) signal analysis applications. The proposed method consists of …