학술논문

Compression, Denoising and Classification of ECG Signals using the Discrete Wavelet Transform and Deep Convolutional Neural Networks
Document Type
Conference
Source
2020 IEEE Signal Processing in Medicine and Biology Symposium (SPMB) Signal Processing in Medicine and Biology Symposium (SPMB), 2020 IEEE. :1-4 Dec, 2020
Subject
Bioengineering
Signal Processing and Analysis
Heart
Heart beat
Noise reduction
Transforms
Electrocardiography
Signal processing
Monitoring
Language
ISSN
2473-716X
Abstract
Electrocardiogram (ECG) is the widely known and most common diagnosis test to analyze the electrical signal in the heart and to detect cardiac anomalies. The functionality of the human heart can be properly monitored, and cardiovascular diseases can be detected through the ECG signal. Early detection of cardiac arrhythmia is also possible by analyzing ECG heartbeats continuously. Millions of people in the world are suffering from cardiac arrhythmia which refers to irregular heartbeats. Accurate detection of irregular heartbeats in the primary stage can be also detected through the ECG signal which is very important to reduce the death caused by heart diseases.