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Fundamental heart sounds analysis using improved complete ensemble EMD with adaptive noise

Altuve Miguel, Suárez Luis, Ardila Jeyson

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

426--439

EN

Phonocardiogram (PCG) recordings contain valuable information about the functioning and state of the heart that is useful in the diagnosis of cardiovascular diseases. The first heart sound (S1) and the second heart sound (S2), produced by the closing of the atrioventricular valves and the closing of the semilunar valves, respectively, are the fundamental sounds of the heart. The similarity in morphology and duration of these heart sounds and their superposition in the frequency domain makes it difficult to use them in computer systems to provide an automatic diagnosis. Therefore, in this paper, we analyzed these heart sounds in the intrinsic mode functions (IMF) domain, which were issued from two time-frequency decomposition techniques, the empirical mode decomposition (EMD) and the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), with the aim of retrieving useful information on an expanded basis. The decomposition of PCG recordings into IMF allows representing the fundamental cardiac sounds in many oscillating components, increasing thus the observability of the system. Moreover, the time-frequency representation of PCG recordings could provide valuable information to automatically detect heart sounds and diagnose pathologies from characteristic patterns of these heart sounds in the IMF. The analysis was made through the variance and Shannon's entropy of the heart sounds, observed in time windows located among different IMF. In addition, we determined the frequencies ranges of the IMF from the decomposition of the PCG recordings using both techniques. Given that the frequency content of S1 and S2 is different but overlap each other, and the duration of these sounds are also different, these heart sounds were represented in different IMF with different variances and entropies, in both techniques, but the ICEEMDAN offers a more consistent decomposition of S1 and S2 (they were concentrated in IMF 4-6). The decomposition of PCG signals into IMF has allowed us to identify the frequency components of the IMF in which these sounds are found.

2

Wykorzystanie algorytmu kompresji sygnału mowy MP-LPC do modelowania przebiegu fonokardiograficznego

Redlarski G., Gradolewski D.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 4

40-45

PL

W artykule przedstawiono nową metodę modelowania dźwięków serca, która może znaleźć zastosowanie w licznych systemach diagnostyki urządzeń medycznych oraz stanowić podstawę opracowania inteligentnego stetoskopu. Przedstawiona propozycja stanowi rozwinięcie algorytmu MP-LPC wykorzystywanego w kompresji sygnału mowy. Wykazano, że do dokładnego modelowania przebiegu fonokardiograficznego, który pozwala na odwzorowywanie różnorodnych stanów patologicznych serca, a tym samym poprawę jednoznaczności interpretacji wybranych chorób, konieczne jest zastosowanie 24-rzędu mianownika transmitancji. Celowa jest również zmiana sposobu wyznaczania funkcji pobudzenia – w wyniku której, zamiast funkcji cross-korelacji, wykorzystywany jest algorytm genetyczny.

EN

In this paper is presented a new heart sound simulation technique, which may find a use in many diagnostic systems in medical devices. This technique can also be a base of an intelligent stethoscope. The proposed algorithm was created as a development of the MP-LPC algorithm, widely used in speech signals coding. It was proved, that the denominator of the 24 order in the transfer function of this model should be applied to build an accurate model of PCG signal. It allows to simulate pathological heart tones, and thereby to gives a possibility of unambiguous interpretation of certain heart disorders. A change in the way of the excitation function generating was also required. Instead of a cross-correlation, a genetic algorithm was implemented.

3

Time frequency analysis of patent ductus arteriosus disease in dogs

Akgün Ö., Varol H. S.

Przegląd Elektrotechniczny

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2012

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R. 88, nr 9b

309-313

EN

This study is based on the analysis of the heart sound signals taken from different auscultation areas of three dogs diagnosed with Patent Ductus Arteriosus (PDA). The analyses were started by introducing the mathematical substructure of the methods used. Then the phonocardiographic signals taken from the three dogs were assessed in terms of time-amplitude (t-a) and frequency amplitude (f-a); subsequently, the components of the signals in time-frequency dimensions were examined. As a result of these analyses, the importance of the auscultation area and time-frequency examination in the diagnosis of the PDA disease was demonstrated.

PL

W artykule zaprezentowano analize shgnałów serca z różnych obszarów ciała trzech psów cierpiących na chorobę Patent Ductus Arteriosus. Przeprowadzono analizę harmoniczną sygnałów w dziedzinie czasu.