Log In Sign Up

Deep Learning-Based Arrhythmia Detection Using RR-Interval Framed Electrocardiograms

by   Song-Kyoo Kim, et al.

Deep learning applied to electrocardiogram (ECG) data can be used to achieve personal authentication in biometric security applications, but it has not been widely used to diagnose cardiovascular disorders. We developed a deep learning model for the detection of arrhythmia in which time-sliced ECG data representing the distance between successive R-peaks are used as the input for a convolutional neural network (CNN). The main objective is developing the compact deep learning based detect system which minimally uses the dataset but delivers the confident accuracy rate of the Arrhythmia detection. This compact system can be implemented in wearable devices or real-time monitoring equipment because the feature extraction step is not required for complex ECG waveforms, only the R-peak data is needed. The results of both tests indicated that the Compact Arrhythmia Detection System (CADS) matched the performance of conventional systems for the detection of arrhythmia in two consecutive test runs. All features of the CADS are fully implemented and publicly available in MATLAB.


page 2

page 3


DENS-ECG: A Deep Learning Approach for ECG Signal Delineation

Objectives: With the technological advancements in the field of tele-hea...

FPGA Implementation of ECG feature extraction using Time domain analysis

An electrocardiogram (ECG) feature extraction system has been developed ...

Arrhythmia Classifier using Binarized Convolutional Neural Network for Resource-Constrained Devices

Monitoring electrocardiogram signals is of great significance for the di...

Multistage Pruning of CNN Based ECG Classifiers for Edge Devices

Using smart wearable devices to monitor patients electrocardiogram (ECG)...

Core-set Selection Using Metrics-based Explanations (CSUME) for multiclass ECG

The adoption of deep learning-based healthcare decision support systems ...

Deep Learning on Retina Images as Screening Tool for Diagnostic Decision Support

In this project, we developed a deep learning system applied to human re...

Choosing a sampling frequency for ECG QRS detection using convolutional networks

Automated QRS detection methods depend on the ECG data which is sampled ...