Abstract Objective: Globally, cardiovascular diseases (CVDs) are one of the most leading
causes of death. In medical screening and diagnostic procedures of CVDs …

Nowadays, healthcare is becoming very modern, and the support of Internet of Things (IoT)
is inevitable in a personal healthcare system. A typical personal healthcare system acquires …

Electrocardiogram (ECG) signals are the biomedical signals commonly used in the
prognosis of cardiovascular diseases. ECG recordings need to be stored and transferred …

The timely identification of cardiovascular diseases is critical for effective intervention, with
the electrocardiogram (ECG) serving as a pivotal diagnostic tool. Recent advancements in …

Automated electrocardiogram (ECG) analysis cannot be employed in clinical practice due to
the accuracy of the present models. Deep Neural Networks (DNNs) are models made up of …

Incalculable numbers of patients in hospitals as a result of COVID-19 made the screening of
heart patients arduous. Patients who need regular heart monitoring were affected the most …

Long-term electrocardiogram (ECG) signal monitoring necessitates a large amount of
memory space for storage, which affects the transmission channel efficiency during real-time …

Cardiovascular diseases (CVDs) are the first cause of death around the world. High-
accuracy heart disease classification can support the decisions about the patients of the …

Objective In cardiac patient-care, compression of long-term ECG data is essential to
minimize the data storage requirement and transmission cost. Hence, this paper presents a …

The electrocardiogram (ECG) signals are commonly used to identify heart complications.
These recordings generate large data that needed to be stored or transferred in …