Human-Assisted vs. Deep Learning Feature Extraction: An Evaluation of ECG Features Extraction Methods for Arrhythmia Classification Using Machine Learning

Human-Assisted vs. Deep Learning Feature Extraction: An Evaluation of ECG Features Extraction Methods for Arrhythmia Classification Using Machine Learning

The success of arrhythmia classification tasks with Machine Learning (ML) algorithms is based on the handcrafting extraction of features from Electrocardiography (ECG) signals. However, feature extraction is a time-consuming trial-and-error approach. Deep Neural Network (DNN) algorithms bypass the p...

Full description

Bibliographic Details
Main Authors: Larissa Montenegro, Mariana Abreu, Ana Fred, Jose M. Machado
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Applied Sciences
Subjects:
heart arrhythmia
convolutional neural network
support vector machines
handcrafted features
deep features
Online Access:https://www.mdpi.com/2076-3417/12/15/7404

Internet

https://www.mdpi.com/2076-3417/12/15/7404

Similar Items