|1/2021 - 5|
View TOC | « Previous Article | Next Article »
A Semi-automatic Heart Sounds Identification Model and Its Implementation in Internet of Things DevicesJUSAK, J. , PUSPASARI, I. , KUSUMAWATI, W. I.
|View the paper record and citations in|
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (3,956 KB) | Citation | Downloads: 696 | Views: 1,059|
Internet of Things, phonocardiography, signal detection, system identification, telemedicine
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
SCOPUS ID: 85106421249
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|
| 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 25] [SCOPUS Times Cited 47]
 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 389] [SCOPUS Times Cited 624]
 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] [SCOPUS Times Cited 498]
 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 10]
 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 19]
 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 19]
 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 49] [SCOPUS Times Cited 63]
 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
 ***, 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
 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
 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 101] [SCOPUS Times Cited 171]
 J. S. Coviello, Auscultation Skills: Breath & Heart Sounds, Wolters Kluwer Health, pp. 56-91, 2014
 A. K. Abbas and R. Bassam, Phonocardiography Signal Processing, Morgan & Claypool, pp. 13-18, 2009
 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 10]
 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 13] [SCOPUS Times Cited 18]
 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 7] [SCOPUS Times Cited 9]
 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 Times Cited 1]
 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 30] [SCOPUS Times Cited 50]
 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 249]
 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 144] [SCOPUS Times Cited 181]
 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 24] [SCOPUS Times Cited 34]
 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 16] [SCOPUS Times Cited 19]
 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 39] [SCOPUS Times Cited 56]
 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 9]
 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 2] [SCOPUS Times Cited 2]
 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 Times Cited 3]
 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 10] [SCOPUS Times Cited 16]
 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 35] [SCOPUS Times Cited 45]
 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 14512] [SCOPUS Times Cited 19800]
 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 1562]
 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 627] [SCOPUS Times Cited 746]
 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.
Web of Science® Citations for all references: 16,273 TCR
SCOPUS® Citations for all references: 24,012 TCR
Web of Science® Average Citations per reference: 493 ACR
SCOPUS® Average Citations per reference: 728 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 2023-06-03 15:23 in 154 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.