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Journal Science Intensive Technologies №10 for 2015 г.
Article in number:
A survey of segmentation methods for phonocardiogram
Authors:
A.W.M. Ahmed - Post-graduate Student, Department of Biomedical and Electronic Systems and Technology, Vladimir State University. E-mail: walid_aed@mail.ru
R.V. Isakov - Ph.D. (Eng.), Associate Professor, Department of Biomedical and Electronic Systems and Technology, Vladimir State University. E-mail: Isakov-RV@mail.ru
L.T. Sushkova - Dr.Sc. (Eng.), Professor, Head of Department of Biomedical and Electronic Systems and Technology, Vladimir State University. E-mail: ludm@vlsu.ru
Abstract:
The functional condition of the cardiovascular system (CVS) is studied using complex instrumental methods to objectively evaluate the biophysical processes in the circulatory system (electrical and mechanical activity of the heart, intracardiac and hemodynamics) [1]. Among them, the most common method is electrocardiography, which allows to evaluate the functioning of the heart using an electrocardiogram (ECG). In this regard, a good addition to electrocardiography is phonocardiograph (PCG), allowing investigating and detecting the presence of disorders of the heart and valve apparatus. The method is based on recording and analyzing sounds produced during contraction and relaxation of the heart, including - heart murmur, which are known to be the first sign occurring disorders of the heart. The source of diagnostic information here is called phonocardiography.
The advantages of the phonocardiography are [50]:
a) The exclusion of subjectivity in the interpretation of heart sounds and heart murmurs;
b) The possibility of registration of the heart sounds and noises in conjunction with electrical and mechanical phenomena that occur during the cardiac cycle.
Analysis of the literature shows that the scientific and practical interest in the processing and analysis of the PCG in terms of its research in the diagnostics cardiovascular system is constantly growing, as evidenced by numerous scientific papers. One of the stages of processing PCG is its segmentation, providing high information content and accuracy of diagnostic information about the CVS.
In this paper the task of comparing analysis of existing methods of segmentation of the main components of phonocardiogram (PCG) in terms of fulfillment of the tasks. Methods of segmentation must ensure reliable efficiency of localization of heart sound S1 and S2 in phonocardiogram. Reviewed examples of practical applications of known segmentation methods from domestic and foreign sources. On the basis of the conducted analysis demonstrated that in solving the problem of segmentation PCG should be prefer such method, which does not require the use of additional biosignals and priori information about any relationships in the original signal. The results of the analysis of the most frequently used methods of segmentation PCG allows to eliminate weaknesses in the known methods for improving the processing systems of the PCG.
Pages: 72-82
References
- Solovev V.V., Kassirskijj G.I. Atlas klinicheskojj fonokardiografii. M.: Medicina. 1983. 296 s.
- Kushakov V.I. Prakticheskaja fonokardiografija: ucheb. posobie. M.: Centralnyjj institut usovershenstvovanija vrachejj. 1989. 48 s.
- Poreva A.S., Fesechko V.A. Obrabotka FKG-signala pri pomoshhi vejjvlet-preobrazovanija // EHlektronika i svjaz. Tematicheskijj vypusk «EHlektronika i nanotekhnologii». 2009. CH. 1. C. 148-155.
- Minkin R.B., Pavlov JU.D. EHlektrokardiografija i fonokardiografija. Izd. 2-e, pererab. i dop. L.: Medicina. Leningradskoe otd-e. 1988. 253 s.
- Koblenc-Mishke A.I. Fonokardiografija: Instrumentalnye metody issledovanija serdechno-sosudistojj sistemy / pod red. T.S. Vinogradovojj. M.: Medicina. 1986. 247 s.
- Moskaljuk V.D., Bogachik N.A., Trefanenko A.G., Bilejjchuk JU.R. Fonokardiograficheskoe pokazateli u bolnykh difteriejj, anginy, kor, infekcionnyjj mononukleoz i ehpidemicheskijj parotit // Bukov. med. vestnik. 2002. № 2. S. 62-65.
- Rybakova M.K. Vozmozhnosti sovremennojj ehkhokardiografii // www.medison.rulsi/art237.
- Dremin I.M., Ivanov O.V., Nechitajjlo V.A. Vejjvlety i ikh ispolzovanie // Uspekhi fizicheskikh nauk. 2001. T. 171. № 5. S. 465-500.
- Ermolenko T.N., SHevchuk V.I. Algoritmy segmentacii s primeneniem bystrogo vejjvlet-preobrazovanija // Stati, prinjatye k publikacii na sajjte Mezhdunar. konf. «Dialog-2003» // www.dialog-21.ru.
- Sorokin V.N., Cyplikhin A.I. Segmentacija i raspoznavanie glasnykh // Informacionnye processy. 2004. T. 4. № 2. S. 202-220.
- Rangajjan R.M. Analiz biomedicinskikh signalov. Prakticheskijj podkhod: per. s angl. pod red. A.P. Nemirko. M.: FIZMATLIT. 2007. 440 s.
- Shaver J. A., Salerni R., Reddy P.S. Normal and abnormal heart sounds in cardiac diagnosis. Part 1: Systolic sounds // Curr. Prob. Cardiol. 1985. V. 10. № 3. P. 1-68.
- Reddy P.S., Salerni R., Shaver I.A. Normal and abnormal heart sounds in cardiac diagnosis. Part 11: Diastolic sounds // Curr. Prob. Cardiol. 1985. V. 10. № 4. P. 1-55.
- Tavel M.E. Clinical Phonocardiography and External Pulse Recording. 3rd Ed. Chicago. IL: Year Book Medical. 1978.
- Lehner R.J., Rangayyan R.M. A three-channel microcomputer system for segmentation and characterization of the phonocardiogram // IEEE Transactions on Biomedical Engineering. 1989. V. BME-34. № 6. R. 485-489.
- Baranek H.L., Lee H.C., Cloutier G., Durand L.-G. Automatic detection of sounds and murmurs in patients with Ionescu-Shiley aortic bioprostheses // Medical and Biological Engineering and Computing. 1989. V. 27. R. 449-455.
- Sankua ChaoAutomatic Phonocardiogram Segmentation Using The Sliding window Autocorrelation Algorithm // Thesis for the degree of master. Carleton University. 2009. 167 p.
- Malarvili M.B., Kamarulafizam I., Hussain S., Helmi D. Heart sound segmentation algorithm based on instantaneous energy of electrocardiogram // In 30th Computers in Cardiology Conference. 2003. R. 327-330.
- Aktualnost primenenija KHolterovskogo monitorirovanija arterialnogo davlenija i EHKG // http://www.incart.ru/text.jsp-id=10473.
- Rajan S., Budd E., Stevenson M., Doraiswami R. Unsupervised and uncued segmentation of the fundamental heart sounds in phonocardiograms using a timescale representation // In Proceedings of 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2006. R. 3732-3735.
- Hamza Cherif L., Debbal S.M., Bereksi-Reguig F. Segmentation of heart sounds and heart murmurs // Journal of Mechanics in Medicine and Biology. 2008. V. 8. № 4. R. 549-559.
- Olmez T., Dokur Z. Classification of heart sounds using an artificial neural network // Pattern Recognit. Lett. 2003. № 24 (January). R. 617-629.
- Barschdorff D., Femmer U., Trowitzsch E. Automatic phonocardiogram signal analysis in infants based on wavelet transforms and artificial neural networks // Computers in Cardiology, 1995. R. 753-756.
- Wang P., Kim Y., Ling L.H., Soh C.B. First heart sound detection for phonocardiogram segmentation // In Proceedings of 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2005. R. 5519-5522.
- Hamza Cheri L., Debbal S.M. Algorithm for detection of the internal components of the heart sounds and their split using a Hilbert transform // Journal of Medical Engineering and Technology. 2013. V. 37(3). R. 220-230.
- Dobeshi I. Desjat lekcijj po vejjvletam. M.: RKHD. 2001.
- Vorobev V.I., Gribunin V.G. Teorija i praktika vejjvlet preobrazovanija. SPb: VUS. 1999.
- Vejjvlet-preobrazovanie // https://ru.wikipedia.org/wiki/ Vejjvlet-preobrazovanie.
- Lekram Bahekar, Abhishek Misal Heart Sounds Segmentation Analysis Using Daubechies Wavelet (db) // International Journal of Research in Advent Technology. 2014. V. 2. № 2. R. 2321-9637.
- Liang H., Lukkarinen S., Hartimo I. A heart sound segmentation algorithm using wavelet decomposition and reconstruction // Proceedings of 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 1997. R. 1630-1633.
- Vebster D.G., Kamyshko I.V., Kalashnik D.A. Medicinskie pribory. Razrabotka i primenenie. M.: Medicinskaja kniga. 2004. 720 s.
- Omran S., Tayel M. A heart sound segmentation and feature extraction algorithm using wavelets // In Proceedings of the Ist International Symposium on Control, Communication and Signal Processing. 2004. R. 235-238.
- Sinicin V.E., Ustjuzhanin D.JU. Issledovanie koronarnykh arterijj // Multispiralnaja kompjuternaja tomografija. 2006. T. 11. №1 // www.consilium_medicum.com/media/bss/06_01/20.shtml.
- Mustecov N.P., Smerdova T.A. Inzhenernye metody mediko-biologicheskikh issledovanijj. KHarkov. 2004. 243 s.
- Cyplikhin A.I., Sorokin V.N. Segmentacija rechi na kardinalnye ehlementy // Informacionnye processy. 2006. T. 6. № 3. S. 177-207.