ECG Compression method based on convolutional autoencoder and discrete wavelet transform

Bekiryazıcı, TahirGürkan, Hakan2021-03-202021-03-2020209781728172064http://doi.org/10.1109/SIU49456.2020.9302056https://hdl.handle.net/20.500.12885/128828th Signal Processing and Communications Applications Conference, SIU 2020 -- 5 October 2020 through 7 October 2020 -- -- 166413In 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. © 2020 IEEE.trinfo:eu-repo/semantics/closedAccessconvolutional auto-encoderdata compressiondiscrete wavelet transformECG signalsECG Compression method based on convolutional autoencoder and discrete wavelet transformEvrisimsel otokodlayici ve ayrik dalgacik donusumu tabanli EKG sikistirma yontemiConference Object10.1109/SIU49456.2020.93020562-s2.0-85100296705N/AN/A