| Citation: |
XIE Yuan, ZHANG Xu, ZOU Tao, MA Ge, SUN Weijun. Blind Separation of Heart-Lung Sound Mixed Signals in Reverberation and Noise Environments[J]. INFORMATION AND CONTROL, 2025, 54(1): 150-160. DOI: 10.13976/j.cnki.xk.2024.3490
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To address the difficulty of using a stethoscope to acquire pure heart and lung sound signals with reverberation and noise in clinical environments, we propose a blind separation algorithm based on the time difference of arrival estimation and iterative gradual optimization technology to explore the separation problem of mixed signals of cardiopulmonary sounds in complex environments with reverberations and noises, assisting clinical doctors in intelligent diagnosis. Firstly, a new model of time-frequency domain cardiopulmonary sound mixed signal is constructed, and the estimation of the mixed matrix is completed using the time difference of arrival estimation. Then, the model parameters are updated using iterative gradual optimization methods to reconstruct the iterative gradual optimization cardiopulmonary sound signals. Simulation experimental results show that the proposed algorithm achieves the separation of cardiopulmonary sound signals under linear and convolutive mixed models. Meanwhile, it has better separation performance and robustness than several popular blind separation algorithms.
| [1] |
FENGQUAN D, BJOERN S, KUN Q, et al. Machine listening for heart status monitoring: Introducing and benchmarking HSS the heart sounds Shenzhen corpus[J]. IEEE Journal of Biomedical and Health Informatics, 2020, 24(7): 2082-2092. doi: 10.1109/JBHI.2019.2955281
|
| [2] |
XIAO B, XU Y Q, BI X L, et al. Follow the sound of children′s heart: A deep-learning-based computer-aided pediatric CHDs diagnosis system[J]. IEEE Internet of Things Journal, 2020, 7(3): 1994-2004. doi: 10.1109/JIOT.2019.2961132
|
| [3] |
YIN D, IVAN W S. Artifact-free wavelet denoising: Non-convex sparse regularization, convex optimization[J]. IEEE Signal Processing Letters, 2015, 22(9): 1364-1368. doi: 10.1109/LSP.2015.2406314
|
| [4] |
ROOZBEH S, IVAN W. S, DAVID M L. SEDA: A tunable Q-factor wavelet-based noise reduction algorithm for multi-talker babble[J]. Speech Communication, 2018, 96: 102-115. doi: 10.1016/j.specom.2017.11.004
|
| [5] |
WANG Z, DA CRUZ J N, WAN F. Adaptive Fourier decomposition approach for lung-heart sound separation[C/OL]//IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications. Piscataway, USA: IEEE, 2015[2023-11-18]. https://ieeexplore.ieee.org/document/7158631. DOI: 10.1109/CIVEMSA.2015.7158631.
|
| [6] |
DIMITRA E, ERIC D M, DANIEL E P, et al. Adaptive noise suppression of pediatric lung auscultations with real applications to noisy clinical settings in developing countries[J]. IEEE Transactions on Biomedical Engineering, 2015, 62(9): 2279-2288. doi: 10.1109/TBME.2015.2422698
|
| [7] |
王晶, 李炜, 洪心睿, 等. 基于改进密度聚类算法的语音信号欠定盲分离[J]. 信息与控制, 2023, 52(6): 784-810. doi: 10.13976/j.cnki.xk.2023.2496
WANG J, LI W, HONG X R, et al. Underdetermined blind separation of speech signals based on an improved density clustering algorithm[J]. Information and Control, 2023, 52(6): 784-810. doi: 10.13976/j.cnki.xk.2023.2496
|
| [8] |
WOODS K J P, JOSH H M. Schema learning for the cocktail party problem[J]. Proceedings of the National Academy of Sciences, 2018, 115(14): E3313-E3322. http://www.xueshufan.com/publication/2792035367
|
| [9] |
ZHOU G, ZHAO Q, ZHANG Y, et al. Linked component analysis from matrices to high-order tensors: Applications to biomedical data[J]. Proceedings of the IEEE, 2016, 104(2): 310-331. doi: 10.1109/JPROC.2015.2474704
|
| [10] |
蔡立羽, 王志中, 李凌, 等. 盲信号处理技术在双通道前臂肌电信号识别中的应用[J]. 信息与控制, 2000, 29(6): 548-552, 558. doi: 10.3969/j.issn.1002-0411.2000.06.011
CAI L Y, WANG Z Z, LI L, et al. Application of blind signal processing technique to two-channel upper limb myoelectric signal identification problem[J]. Information and Control, 2000, 29(6): 548-552, 558. doi: 10.3969/j.issn.1002-0411.2000.06.011
|
| [11] |
MAYORGA P, VALDEZ J A, DRUZGALSKI C, et al. Separation of cardiopulmonary acoustic indicators[C]//Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges. Piscataway, USA: IEEE, 2019[2023-11-04]. https://ieeexplore.ieee.org/abstract/document/8717322. DOI: 10.1109/GMEPE-PAHCE.2019.8717322.
|
| [12] |
COMON P. Independent component analysis, a new concept?[J]. Signal Processing, 1994, 36(3): 287-314. doi: 10.1016/0165-1684(94)90029-9
|
| [13] |
HIROSHI S, HIROKAZU K, SHOKO A, et al. Multichannel extensions of non-negative matrix factorization with complex-valued data[J]. IEEE Transactions on Audio, Speech, and Language Processing, 2013, 21(5): 971-982. doi: 10.1109/TASL.2013.2239990
|
| [14] |
DAICHI K, KOHEI Y. Consistent independent low-rank matrix analysis for determined blind source separation[J]. EURASIP Journal on Advances in Signal Processing, 2020(1): 46-35. http://doc.paperpass.com/foreign/rgPrep2020287921863.html
|
| [15] |
解元, 邹涛, 孙为军, 等. 面向卷积混叠环境下的盲源分离新方法[J]. 自动化学报, 2023, 49(5): 1062-1072.
XIE Y, ZOU T, SUN W J, et al. Novel blind source separation method for convolutive mixed environment[J]. Acta Automatica Sinica, 2023, 49(5): 1062-1072.
|
| [16] |
CHIEN J C, HUANG M C, LIN Y D, et al. A study of heart sound and lung sound separation by independent component analysis technique[C]//International Conference of the IEEE Engineering in Medicine and Biology Society. Piscataway, USA: IEEE, 2006: 5708-5711.
|
| [17] |
AYARI F, KSOURI M, ALOUANI A. A new scheme for automatic classification of pathologic lung sounds[J]. International Journal of Computer Science Issues, 2012, 9(4): 448-459. http://www.researchgate.net/profile/Mekki_Ksouri/publication/268063485_A_new_scheme_for_automatic_classification_of_pathologic_lung_sounds/links/5487ed120cf289302e2ee386/A-new-scheme-for-automatic-classification-of-pathologic-lung-sounds.pdf
|
| [18] |
ASHOK M, ISHAN S, HONG T, et al. A noise reduction technique based on nonlinear kernel function for heart sound analysis[J]. IEEE Journal of Biomedical and Health Informatics, 2018, 22(3): 775-784. doi: 10.1109/JBHI.2017.2667685
|
| [19] |
XIE Y, XIE K, XIE S L. Underdetermined blind source separation for heart sound using higher-order statistics and sparse representation[J]. IEEE Access, 2019, 7: 87606-87616. doi: 10.1109/ACCESS.2019.2925896
|
| [20] |
CANADAS-QUESADA F J, RUIZ-REYES N, CARABIAS-ORTI J, et al. A non-negative matrix factorization approach based on spectro-temporal clustering to extract heart sounds[J]. Applied Acoustics, 2017, 125(10): 7-19. http://www.onacademic.com/detail/journal_1000039880678910_434d.html
|
| [21] |
SHAH G, KOCH P, PAPADIAS C B. On the blind recovery of cardiac and respiratory sounds[J]. IEEE Journal of Biomedical and Health Informatics, 2014, 19(1): 151-157. http://ieeexplore.ieee.org/document/6879427/
|
| [22] |
LIN C S, HASTING E. Blind source separation of heart and lung sounds based on nonnegative matrix factorization[C]//International Symposium on Intelligent Signal Processing and Communication Systems, 2013: 731-736.
|
| [23] |
XIE Y, XIE K, YANG Q Y, et al. Reverberant blind separation of heart and lung sounds using nonnegative matrix factorization and auxiliary function technique[J/OL]. Biomedical Signal Processing and Control, 2021, 69[2023-10-19]. https://www.sciencedirect.com/science/article/pii/S1746809421004961.
|
| [24] |
CHANDNA P, MIRON M, JANER J, et al. Monoaural audio source separation using deep convolutional neural networks[C]//International Conference on Latent Variable Analysis and Signal Separation. Berlin, Germany: Springer, 2017: 258-266.
|
| [25] |
GROOBY E, SITAULA C, FATTAHI D, et al. Real-time multi-level neonatal heart and lung sound quality assessment for telehealth applications[J]. IEEE Access, 2022, 10: 10934-10948. doi: 10.1109/ACCESS.2022.3144355
|
| [26] |
GROOBY E, SITAULA C, FATTAHI D, et al. Noisy neonatal chest sound separation for high-quality heart and lung sounds[J]. IEEE Journal of Biomedical and Health Informatics, 2023, 27(6): 2635-2346. doi: 10.1109/JBHI.2022.3215995
|
| [27] |
Babu K A, BARATHRAM R. Automatic recognition of fundamental heart sound segments from pcg corrupted with lung sounds and speech[J]. IEEE Access, 2020, 8: 179983-179994. doi: 10.1109/ACCESS.2020.3023044
|
| [28] |
BLANDIN C, OZEROV A, VINCENT E. Multi-source TDOA estimation in reverberant audio using angular spectra and clustering[J]. Signal Processing, 2012, 92(8): 1950-1960. doi: 10.1016/j.sigpro.2011.09.032
|
| [29] |
ROBIN S, NOBUTAKA O. Fast and stable blind source separation with RANK-1 updates[C]//IEEE International Conference on Acoustics, Speech and Signal Processing. Piscataway, USA: IEEE, 2020: 236-240.
|
| [30] |
NOBUTAKA O. Stable and fast update rules for independent vector analysis based on auxiliary function technique[C]//IEEE Workshop on Applications of Signal Processing to Audio and Acousticsg. Piscataway, USA: IEEE, 2011: 189-192.
|
| [31] |
VINCENT E, GRIBONVAL R, FEVOTTE C. Performance measurement in blind audio source separation[J]. IEEE Transactions on Audio, Speech, and Language Processing, 2006, 14(4): 1462-1469. http://hal.archives-ouvertes.fr/docs/00/54/42/30/PDF/vincent_TASLP06bis.pdf
|
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