ECG Compression method based on convolutional autoencoder and discrete wavelet transform
- Resource Type
- Conference
- Authors
- Bekiryazici, Tahir; Gurkan, Hakan
- Source
- 2020 28th Signal Processing and Communications Applications Conference (SIU) Signal Processing and Communications Applications Conference (SIU), 2020 28th. :1-4 Oct, 2020
- Subject
- Communication, Networking and Broadcast Technologies
Engineering Profession
Signal Processing and Analysis
Electrocardiography
Convolution
Discrete wavelet transforms
Nanoelectromechanical systems
Graphics processing units
Decoding
Databases
ECG signals
data compression
convolutional auto-encoder
discrete wavelet transform
- Language
In this work, a compression method based on one dimensional convolutional autocoder architecture and wavelet transform is proposed for the compression of ECG signals. The proposed method is tested on the MIT-BIH Arrhythmia Database and its performance is evaluated with respect to compression ratio (CR) and mean-independent percentage mean square difference (MPRD). Experimental results showed that the proposed method achieves an average CR value of 32.27:1 with an averages MPRD of %18.91.