A review of automated methods for detection of myocardial ischemia and infarction using electrocardiogram and electronic health records

S Ansari, N Farzaneh, M Duda, K Horan… - IEEE reviews in …, 2017 - ieeexplore.ieee.org
There is a growing body of research focusing on automatic detection of ischemia and
myocardial infarction (MI) using computer algorithms. In clinical settings, ischemia and MI …

[HTML][HTML] ECG-based heartbeat classification for arrhythmia detection: A survey

EJS Luz, WR Schwartz, G Cámara-Chávez… - Computer methods and …, 2016 - Elsevier
An electrocardiogram (ECG) measures the electric activity of the heart and has been widely
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …

[PDF][PDF] QRS detection and heart rate variability analysis: A survey

RJ Oweis, BO Al-Tabbaa - Biomed. Sci. Eng, 2014 - academia.edu
Cardiac-related diseases have been one major cause of death for an ever increasing
number of patients over the last few decades throughout the world. In response, automatic …

A novel ECG signal classification method using DEA-ELM

A Diker, E Avci, E Tanyildizi, M Gedikpinar - Medical hypotheses, 2020 - Elsevier
Electrocardiogram (ECG) signals represent the electrical mobility of the human heart. In
recent years, computer-aided systems have helped to cardiologists in the detection …

A pyramid-like model for heartbeat classification from ECG recordings

J He, L Sun, J Rong, H Wang, Y Zhang - PloS one, 2018 - journals.plos.org
Heartbeat classification is an important step in the early-stage detection of cardiac
arrhythmia, which has been identified as a type of cardiovascular diseases (CVDs) affecting …

Feature extraction of ECG signal by using deep feature

A Diker, A Engin - 2019 7th International Symposium on Digital …, 2019 - ieeexplore.ieee.org
The analysis and classification of Electrocardiogram (ECG) signals have become very
important tool to diagnose of heart disorders. Computer-aided techniques are generally …

Automated detection of heart ailments from 12‐lead ECG using complex wavelet sub‐band bi‐spectrum features

RK Tripathy, S Dandapat - Healthcare technology letters, 2017 - Wiley Online Library
The complex wavelet sub‐band bi‐spectrum (CWSB) features are proposed for detection
and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle …

A methodology for embedded classification of heartbeats using random projections

R Braojos, G Ansaloni, D Atienza - 2013 Design, Automation & …, 2013 - ieeexplore.ieee.org
Smart Wireless Body Sensor Nodes (WBSNs) are a novel class of unobtrusive, battery-
powered devices allowing the continuous monitoring and real-time interpretation of a …

An extensible framework for ECG anomaly detection in wireless body sensor monitoring systems

L Sun, J He - International Journal of Sensor Networks, 2019 - inderscienceonline.com
Automatic anomaly detection from the sensor streams of the Electrocardiography requires
online techniques of data stream processing and analysis. The significant increase in the …

Early classification of pathological heartbeats on wireless body sensor nodes

R Braojos, I Beretta, G Ansaloni, D Atienza - Sensors, 2014 - mdpi.com
Smart Wireless Body Sensor Nodes (WBSNs) are a novel class of unobtrusive, battery-
powered devices allowing the continuous monitoring and real-time interpretation of a …