https://scholars.lib.ntu.edu.tw/handle/123456789/557631
標題: | Phonocardiography signals compression with deep convolutional autoencoder for telecare applications | 作者: | Chien, Y.-R. Hsu, K.-C. HEN-WAI TSAO |
關鍵字: | Autoencoder; Deep learning; One-dimensional convolutional neural network (1D CNN); Phonocardiogram (PCG); Signal compression; Telecare | 公開日期: | 2020 | 卷: | 10 | 期: | 17 | 來源出版物: | Applied Sciences (Switzerland) | 摘要: | Phonocardiography (PCG) signals that can be recorded using the electronic stethoscopes play an essential role in detecting the heart valve abnormalities and assisting in the diagnosis of heart disease. However, it consumes more bandwidth when transmitting these PCG signals to remote sites for telecare applications. This paper presents a deep convolutional autoencoder to compress the PCG signals. At the encoder side, seven convolutional layers were used to compress the PCG signals, which are collected on the patients in the rural areas, into the feature maps. At the decoder side, the doctors at the remote hospital use the other seven convolutional layers to decompress the feature maps and reconstruct the original PCG signals. To confirm the effectiveness of our method, we used an open accessed dataset on PHYSIONET. The achievable compress ratio (CR) is 32 when the percent root-mean-square difference (PRD) is less than 5%. © 2020 by the authors. |
URI: | https://www.scopus.com/inward/record.url?eid=2-s2.0-85090004136&partnerID=40&md5=4103f499b738631efb96caa7eaac3645 https://scholars.lib.ntu.edu.tw/handle/123456789/557631 |
DOI: | 10.3390/app10175842 |
顯示於: | 電機工程學系 |
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