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Article

Temporal Convolutional Network Connected with an Anti-Arrhythmia Hidden Semi-Markov Model for Heart Sound Segmentation

1
Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(20), 7049; https://doi.org/10.3390/app10207049
Submission received: 7 September 2020 / Revised: 6 October 2020 / Accepted: 7 October 2020 / Published: 11 October 2020

Abstract

Heart sound segmentation (HSS) is a critical step in heart sound processing, where it improves the interpretability of heart sound disease classification algorithms. In this study, we aimed to develop a real-time algorithm for HSS by combining the temporal convolutional network (TCN) and the hidden semi-Markov model (HSMM), and improve the performance of HSMM for heart sounds with arrhythmias. We experimented with TCN and determined the best parameters based on spectral features, envelopes, and one-dimensional CNN. However, the TCN results could contradict the natural fixed order of S1-systolic-S2-diastolic of heart sound, and thereby the Viterbi algorithm based on HSMM was connected to correct the order errors. On this basis, we improved the performance of the Viterbi algorithm when detecting heart sounds with cardiac arrhythmias by changing the distribution and weights of the state duration probabilities. The public PhysioNet Computing in Cardiology Challenge 2016 data set was employed to evaluate the performance of the proposed algorithm. The proposed algorithm achieved an F1 score of 97.02%, and this result was comparable with the current state-of-the-art segmentation algorithms. In addition, the proposed enhanced Viterbi algorithm for HSMM corrected 30 out of 30 arrhythmia errors after checking one by one in the dataset.
Keywords: heart sound segmentation; temporal convolutional network; hidden semi-Markov model; cardiac arrhythmia heart sound segmentation; temporal convolutional network; hidden semi-Markov model; cardiac arrhythmia

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MDPI and ACS Style

Yin, Y.; Ma, K.; Liu, M. Temporal Convolutional Network Connected with an Anti-Arrhythmia Hidden Semi-Markov Model for Heart Sound Segmentation. Appl. Sci. 2020, 10, 7049. https://doi.org/10.3390/app10207049

AMA Style

Yin Y, Ma K, Liu M. Temporal Convolutional Network Connected with an Anti-Arrhythmia Hidden Semi-Markov Model for Heart Sound Segmentation. Applied Sciences. 2020; 10(20):7049. https://doi.org/10.3390/app10207049

Chicago/Turabian Style

Yin, Yibo, Kainan Ma, and Ming Liu. 2020. "Temporal Convolutional Network Connected with an Anti-Arrhythmia Hidden Semi-Markov Model for Heart Sound Segmentation" Applied Sciences 10, no. 20: 7049. https://doi.org/10.3390/app10207049

APA Style

Yin, Y., Ma, K., & Liu, M. (2020). Temporal Convolutional Network Connected with an Anti-Arrhythmia Hidden Semi-Markov Model for Heart Sound Segmentation. Applied Sciences, 10(20), 7049. https://doi.org/10.3390/app10207049

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