Electrocardiogram (ECG) signals are often used to diagnose cardiac status. However, most
of the existing ECG diagnostic methods only use the time-domain information, resulting in …

The existing heart failure risk prediction models are developed based on machine learning
predictors. The objective of this study is to identify the key risk factors that affect the survival …

Accepted: 10 February 2023 The diagnosis techniques of diseases which are based on
biomedical signals processing are constantly evolving, cardiovascular diseases are no …

Blind source separation (BSS) is a widely adopted approach for processing biomedical
signals, particularly electroencephalography (EEG) signals, which indicate the electrical …

Abstract Number of cardiac conditions have been associated with abnormal heartbeat
(arrhythmia) such as ventricular fibrillation (Vfib), ventricular flutter (Vfl), and ventricular …

Biomedical signals, such as an electrocardiogram (ECG), have been included in wearable
platforms for biometric reasons due to the rapid expansion of apps and technology capable …

At the present, the diagnosis of the cardiovascular diseases knew a great evolution, this
progress was the result of the development of the techniques used in the diagnosis, which …

The rapid proliferation of wearable applications and technologies capable of acquiring
biomedical signals has prompted the incorporation of biomedical signals, such as the …

The adoption of biomedical signals such as the electrocardiogram (ECG) for biometric is
rising in tandem with the increased attention to wearable devices. However, despite its …

One important step in the process of identifying EKG signals is feature extraction, where the
obtained features characterize the condition of the heart. The condition of the heart can be …