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Heart sound signal recovery based on time series signal prediction using a recurrent neural network in the long short-term memory model

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Abstract

In this research, we propose a method for recovering heart sound signals that comprises the long short-term memory prediction model based on the recurrent neuron network architecture. The complete heart sound signal is used to implement a prediction model to recover damaged or incomplete heart sound signals. Root mean square errors (RMSEs) and Pearson’s correlation coefficients are used for numerical evaluation. The signals of 13 out of 15 subjects are considerably improved, with the RMSE being as low as 0.03 ± 0.04. Using the Pearson correlation coefficients to estimate the degree of signal recovery, the highest coefficient of correlation between the original and recovered time-domain waveforms is 0.93, and that between the corresponding spectra is 0.967. Waveforms and spectra are used to compare the results graphically. The recovered signal more closely fits the original signal than the interfered signal. Additionally, excess frequency components in the recovered spectra are found to be filtered out and important features retained. Thus, the proposed method not only recovers incomplete or disturbed signals but also has the effect of a filter.

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Acknowledgements

This work was supported in part by the “Allied Advanced Intelligent Biomedical Research Center, STUST” from Higher Education Sprout Project, Ministry of Education, Taiwan and in part by the Small Business Innovation Research (SBIR) of Taiwan under No.1Z1070773.

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Authors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan

    Zhi-Hao Wang & Gwo-Jia Jong

  2. Department of Computer Science and Information Engineering, Southern Taiwan University of Science and Technology, Tainan, Taiwan

    Gwo-Jiun Horng & Tz-Heng Hsu

  3. Department of Electrical Engineering, Universitas Negeri Malang, Malang, Indonesia

    A. Aripriharta

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  1. Zhi-Hao Wang
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  2. Gwo-Jiun Horng
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  3. Tz-Heng Hsu
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  4. A. Aripriharta
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  5. Gwo-Jia Jong
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Correspondence to Gwo-Jiun Horng.

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Wang, ZH., Horng, GJ., Hsu, TH. et al. Heart sound signal recovery based on time series signal prediction using a recurrent neural network in the long short-term memory model. J Supercomput 76, 8373–8390 (2020). https://doi.org/10.1007/s11227-019-03096-x

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