In this work, arrhythmia appearing with the presence of abnormal heart electrical activity is
efficiently recognized and classified. A novel method is proposed for accurate recognition …

The most important ECG marker for the diagnosis of ischemia or infarction is a change in the
ST segment. Baseline wander is a typical artifact that corrupts the recorded ECG and can …

We developed a novel method for QRS complex and P wave detection in the
electrocardiogram (ECG) signal. The approach reconstructs two different signals for the …

This study examines the effect of mental workload on the electrocardiogram (ECG) of
participants driving the Lane Change Task (LCT). Different levels of mental workload were …

In order to detect multiple sclerosis (MS) subjects from healthy controls (HCs) in magnetic
resonance imaging, we developed a new system based on machine learning. The MS …

The electrocardiogram (ECG) is a standard cost-efficient and non-invasive tool for the early
detection of various cardiac diseases. Quantifying different timing and amplitude features of …

Electrocardiogram (ECG) acquired by wearable devices is increasingly used for healthcare
applications. However, the ECG signals are severely corrupted by various noises (eg …

The correct identification of individuals through different biometric traits is becoming
increasingly important. Apart from traditional biomarkers (like fingerprints), many alternative …

Electrocardiogram (ECG) is a non-invasive and economical diagnostic tool for detecting
myocardial infarction (MI). The occurrence of a heart attack causes distortions in the ECG …

Electrocardiogram (ECG) signals quality can be seriously affected by artifacts such as
electromyogram (EMG), negatively impacting its clinical value. Various denoising methods …