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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  1/2021 - 5

A Semi-automatic Heart Sounds Identification Model and Its Implementation in Internet of Things Devices

JUSAK, J. See more information about JUSAK, J. on SCOPUS See more information about JUSAK, J. on IEEExplore See more information about JUSAK, J. on Web of Science, PUSPASARI, I. See more information about  PUSPASARI, I. on SCOPUS See more information about  PUSPASARI, I. on SCOPUS See more information about PUSPASARI, I. on Web of Science, KUSUMAWATI, W. I. See more information about KUSUMAWATI, W. I. on SCOPUS See more information about KUSUMAWATI, W. I. on SCOPUS See more information about KUSUMAWATI, W. I. on Web of Science
 
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Download PDF pdficon (3,956 KB) | Citation | Downloads: 1 | Views: 3

Author keywords
Internet of Things, phonocardiography, signal detection, system identification, telemedicine

References keywords
heart(16), signal(8), sounds(7), healthcare(6), access(6), time(5), system(5), sound(5), processing(5), security(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-02-28
Volume 21, Issue 1, Year 2021, On page(s): 45 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.01005
Web of Science Accession Number: 000624018800005

Abstract
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Identification of heart sound signals in the form of a phonocardiogram (PCG) has recently attracted the attention of many researchers along with the development of small devices and global Internet connection in a way to offer automatic illness detection and monitoring. In this work, we propose a semi-automatic envelope-based heart sounds identification method called the Largest Interval Heart Sounds Detection (LiHSD) that exploits the superiority of the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and the cubic spline interpolation to discover several heart sounds' components such as period and location of S1 and S2, an interval of a cardiac cycle, and to obtain the duration and location of murmurs. Evaluation of the proposed system over several life sample data showed promising results comparable to the previous models. The algorithm was able to capture the largest interval of S1 and S2. The examination for normal heart sounds exhibited detection accuracy 98 percent, whereas for anomaly heart sounds samples the detection accuracy ranging from 89 percent to 97.5 percent. Furthermore, the proposed system has been successfully implemented in a real Internet of Things device while eyeing its contribution to the future of the smart healthcare system.


References | Cited By  «-- Click to see who has cited this paper

[1] H. Ren, H. Jin, C. Chen, H. Ghayvat, and W. Chen, "A novel cardiac auscultation monitoring system based on wireless sensing for healthcare," IEEE J. Transl. Eng. Heal. Med., vol. 6, no. April, pp. 1-12, 2018.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 24]


[2] S. B. Baker, W. Xiang, and I. Atkinson, "Internet of Things for smart healthcare: technologies, challenges, and opportunities," IEEE Access, vol. 5, pp. 26521-26544, 2017.
[CrossRef] [Web of Science Times Cited 171] [SCOPUS Times Cited 266]


[3] Y. Yin, Y. Zeng, X. Chen, and Y. Fan, "The Internet of Things in healthcare: An overview," J. Ind. Inf. Integr., vol. 1, pp. 3-13, 2016.
[CrossRef] [Web of Science Times Cited 173] [SCOPUS Times Cited 264]


[4] J. Jusak and I. Puspasari, "Wireless tele-auscultation for phonocardiograph signal recording through Zigbee networks," in Proc. APWiMob 2015 - IEEE Asia Pacific Conf. Wirel. Mob., pp. 95-100, 2016.
[CrossRef] [SCOPUS Times Cited 6]


[5] C. Rotariu, V. Manta, H. Costin, "Wireless remote monitoring System for patients with cardiac pacemakers," 2012 International Conference and Exposition on Electrical and Power Engineering (EPE), 2012, Iasi, Romania, pp: 845-848, Oct. 25-27, 2012,
[CrossRef] [SCOPUS Times Cited 15]


[6] H. Costin, C. Rotariu, I. Alexa, et al., "TELEMON - A complex system for real time medical telemonitoring," 11th Int. Congress of the IUPESM/World Congress on Medical Physics and Biomedical Engineering, Munich, Germany, Sept. 07-12, Vol. 25, PT 5, Book Series: IFMBE Proceedings, pp. 92-96, Part 5, Published 2009,
[CrossRef] [SCOPUS Times Cited 16]


[7] A. Limaye and T. Adegbija, "HERMIT: A benchmark suite for the Internet of Medical Things," IEEE Internet of Things J., vol. 5, no. 5, pp. 4212-4222, 2018.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 19]


[8] U.S. Department of Health and Human Services, "HIPAA security series: 1 security 101 for covered entities," Centers for Medicare & Medicade Sercices, vol. 2, pp. 1-11, 2007

[9] ***, The European Parliament and The Council of European Union, "Directive 95/46/EC of the European Parliament and of the council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data," Official Journal L281, pp. 31-50, 1995

[10] J. Jusak and S.S. Mahmoud, "Novel and Low Processing Time ECG Security Method Suitable for Sensor Node Platforms," International Journal of Communication Networks and Information Security, vol. 10, no. 1, pp. 213-222, 2018

[11] K. H. Yeh, "A Secure IoT-based healthcare system with body sensor networks," IEEE Access, vol. 4, pp. 10288-10299, 2016.
[CrossRef] [Web of Science Times Cited 56] [SCOPUS Times Cited 95]


[12] J. S. Coviello, Auscultation Skills: Breath & Heart Sounds, Wolters Kluwer Health, pp. 56-91, 2014

[13] A. K. Abbas and R. Bassam, Phonocardiography Signal Processing, Morgan & Claypool, pp. 13-18, 2009

[14] J. Jusak, I. Puspasari, and P. Susanto, "Heart murmurs extraction using the complete Ensemble Empirical Mode Decomposition and the Pearson distance metric," in Proc. 2016 Int. Conf. Inf. Commun. Technol. Syst. ICTS 2016, no. 058, pp. 140-145, 2017.
[CrossRef] [SCOPUS Times Cited 7]


[15] S. H. Kang, B. Joe, Y. Yoon, G. Y. Cho, I. Shin, and J. W. Suh, "Cardiac auscultation using smartphones: Pilot study," JMIR mHealth uHealth, vol. 6, no. 2, pp. 1-11, 2018.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 8]


[16] K. V. I. Chatzakis and I. G. ssilakis, C. Lionis, "Electronic health record with computerized decision support tools for the purposes of a pediatric cardiovascular heart disease screening program in crete," Comput. Methods Programs Biomed., vol. 159, pp. 159-166, 2018.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 7]


[17] I. S. Ateeq, K. Hameed, M. Khowaja, and S. H. Khan, "Design and implementation of digital tele stethoscope," in World Congress on Medical Physics and Biomedical Engineering 2018, 2019, pp. 867-873.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Record]


[18] S. Ismail, I. Siddiqi, and U. Akram, "Localization and classification of heart beats in phonocardiography signals - a comprehensive review," EURASIP J. Adv. Signal Process., vol. 2018, no. 1, 2018.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 15]


[19] H. Liang, S. Lukkarinen, and I. Hartimo, "Heart sounds segmentation algorithm based on heart sounds envelogram," Comput. Cardiol., no. October 1997, pp. 105-108, 1997.
[CrossRef] [Web of Science Times Cited 230]


[20] S. Choi and Z. Jiang, "Comparison of envelope extraction algorithms for cardiac sound signal segmentation," Expert Syst. with Appl., vol. 34, no. 2, pp. 1056-1069, 2008.
[CrossRef] [Web of Science Times Cited 134] [SCOPUS Times Cited 164]


[21] N. Giordano and M. Knaflitz, "A novel method for measuring the timing of heart sounds components through digital phonocardiography," Sensors, vol. 19, no. 8, pp. 1-16, 2019.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 13]


[22] V. N. Varghees, K.I Ramachandran, and K.P. Soman, "Wavelet-based fundamental heart sound recognition method using morphological and interval features," Healthcare Technology Letters, vol. 5, no. 3., pp. 81-87, 2018.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 12]


[23] B. Ergen, Y. Tatar, and H. O. Gulcur, "Time-frequency analysis of phonocardiogram signals using wavelet transform: a comparative study," Comput. Methods Biomech. Biomed. Engin., vol. 15, no. 4, pp. 371-381, 2012.
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 40]


[24] A. Atbi, S. M. Debbal, F. Meziani, and A. Meziane, "Separation of heart sounds and heart murmurs by Hilbert transform envelogram," J. Med. Eng. Technol., vol. 37, no. 6, pp. 375-387, 2013.
[CrossRef] [SCOPUS Times Cited 7]


[25] D. Mandal, A. Maity, and I.S. Misra, "Low cost portable solution for real-time complete detection and analysis of heart sound components," Wireless Personal Communications, vol. 107, pp. 523-547, 2019.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Record]


[26] I. Puspasari, W. I. Kusumawati, E. S. Oktarina and J. Jusak, "A New Heart Sound Signal Identification Approach Suitable for Smart Healthcare Systems," in 2019 2nd International Conference on Applied Engineering (ICAE), Batam, Indonesia, 2019, pp. 1-6,
[CrossRef] [SCOPUS Record]


[27] F. Dong et al., "Machine Listening for Heart Status Monitoring: Introducing and Benchmarking HSS - The Heart Sounds Shenzhen Corpus," IEEE Journal of Biomedical and Health Informatics, vol. 24, no. 7, pp. 2082-2092, July 2020,
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Record]


[28] P. T. Krishnan, P. Balasubramanian, S. Umapathy, "Automated heart sound classification system from unsegmented phonocardiogram (PCG) using deep neural network," Phys Eng Sci Med 43, pp. 505-515 2020.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 9]


[29] N. E. Huang et al., "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis," Proc. R. Soc. London. Ser. A Math. Phys. Eng. Sci., vol. 454, no. 1971, pp. 903-995, 1998.
[CrossRef] [Web of Science Times Cited 11671] [SCOPUS Times Cited 15831]


[30] M. E. Torres, M. A. Colominas, G. Schlotthauer, and P. Flandrin, "A complete ensemble empirical mode decomposition with adaptive noise," in 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, pp. 4144-4147.
[CrossRef] [SCOPUS Times Cited 843]


[31] M. A. Colominas, G. Schlotthauer, and M. E. Torres, "Improved complete ensemble EMD: A suitable tool for biomedical signal processing," Biomed. Signal Process. Control, vol. 14, no. 1, pp. 19-29, 2014.
[CrossRef] [Web of Science Times Cited 337] [SCOPUS Times Cited 422]


[32] A. K. Dwivedi, S. A. Imtiaz, and E. R. Villegas, "Algorithms for automatic analysis and classification of heart sounds-a systematic review," IEEE Access, vol. 7, pp.8316-8345, 2019.
[CrossRef]




References Weight

Web of Science® Citations for all references: 12,865 TCR
SCOPUS® Citations for all references: 18,083 TCR

Web of Science® Average Citations per reference: 390 ACR
SCOPUS® Average Citations per reference: 548 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-04-15 14:41 in 177 seconds.




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