Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

A Lyon, A Mincholé, JP Martínez… - Journal of The …, 2018 - royalsocietypublishing.org
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …

Unsupervised ECG analysis: A review

K Nezamabadi, N Sardaripour, B Haghi… - IEEE Reviews in …, 2022 - ieeexplore.ieee.org
Electrocardiography is the gold standard technique for detecting abnormal heart conditions.
Automatic detection of electrocardiogram (ECG) abnormalities helps clinicians analyze the …

Computer-aided arrhythmia diagnosis with bio-signal processing: A survey of trends and techniques

SMP Dinakarrao, A Jantsch, M Shafique - ACM Computing Surveys …, 2019 - dl.acm.org
Signals obtained from a patient, ie, bio-signals, are utilized to analyze the health of patient.
One such bio-signal of paramount importance is the electrocardiogram (ECG), which …

Low cost, portable ECG monitoring and alarming system based on deep learning

SM Ahsanuzzaman, T Ahmed… - 2020 IEEE Region 10 …, 2020 - ieeexplore.ieee.org
Electrocardiogram (ECG) has been the golden standard for the detection of cardiovascular
disease for many years. Any electrical impulse disruption that causes the heart to the …

A multistage deep belief networks application on arrhythmia classification

G Altan, Y Kutlu, N Allahverdı - International Journal of Intelligent …, 2016 - dergipark.org.tr
An electrocardiogram (ECG) is a biomedical signal type that determines the normality and
abnormality of heart beats using the electrical activity of the heart and has a great …

Arrhythmia detection using amplitude difference features based on random forest

J Park, S Lee, K Kang - … Conference of the IEEE Engineering in …, 2015 - ieeexplore.ieee.org
A number of promising studies have been proposed for diagnosing arrhythmia, using
classification techniques based on a variety of heartbeat features by the interpretation of …

Power transmission and workload balancing policies in eHealth mobile cloud computing scenarios

J Pagán, M Zapater, JL Ayala - Future Generation Computer Systems, 2018 - Elsevier
Abstract The Internet of Things (IoT) holds big promises for healthcare, especially in
proactive personal eHealth. Prediction of symptomatic crises in chronic diseases in the IoT …

Real‐Time Heart Arrhythmia Detection Using Apache Spark Structured Streaming

S Ilbeigipour, A Albadvi… - Journal of Healthcare …, 2021 - Wiley Online Library
One of the major causes of death in the world is cardiac arrhythmias. In the field of
healthcare, physicians use the patient's electrocardiogram (ECG) records to detect …

Optimizing Deep Neuro-fuzzy Network for ECG Medical Big Data through Integration of Multiscale Features

X Wang, J Lv, BG Kim… - … on Fuzzy Systems, 2024 - ieeexplore.ieee.org
Electrocardiogram (ECG) analysis and diagnosis are important auxiliary means for
preventing and detecting cardiovascular diseases. Traditional approaches often face …

[PDF][PDF] Arrhythmia classification using waveform ECG signals

Y Kutlu, G Altan, N Allahverdi - Int. Conf. Advanced Technology & …, 2016 - academia.edu
An electrocardiogram (ECG) is a non-linear and nonstationary diagnostic biomedical signal
that has a great importance for cardiac disorders. The computer-assisted analysis of …