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

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

Designing power aware wearable devices is the main key in building compact size
autonomous smart devices to successfully connect health Internet of things solutions. With …

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 …

In this paper, we propose a new automated quality-aware electrocardiogram (ECG) beat
classification method for effective diagnosis of ECG arrhythmias under unsupervised …

Long-term electrocardiogram (ECG) signals recorded in an intensive care unit (ICU) are
often corrupted by severe motion and noise artifacts (MNA), which may lead to many false …

This study presents a new QRS detection algorithm making use of the background noise that
is inevitably present in electrocardiogram (ECG) recordings. The algorithm suppresses …

The assessment of signal quality has been a research topic since the late 1970s, as it is
mainly related to the problem of false alarms in bedside monitors in the intensive care unit …

Nowadays, use of the dynamic electrocardiogram (ECG) has developed rapidly because of
the wide application of wearable devices [1]–[3]. Most ECG-based diagnostic algorithms …