Heart Sound Segregation from Breath Sound Using Hilbert Variational Decomposition
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Abstract
23As the cardiovascular ailments are among the top causes for increasing deaths around the globe, a hustle free heart sound (i.e., without the disturbance which is created by interfering lung sounds) is significant. The objective of this study is to segregate the lung sound from the breath sound in order to get a distraction-free heart sound for medical purposes. Quite often even the most experienced clinicians make mistakes in recognizing the heart sounds (HS) which may lead to a misdiagnosis of HS for ailments while some innocent murmurs may be diagnosed as a severe threat which leads to the expensive and many a time tiresome medical test. In this study, the Hilbert Variational method (HVD) is employed for the suppression of lung sounds (LS) from heart sounds. The HVD decomposes the signal in p number of sub-signals (modes), without altering the phase information of the signal. Then the modes with lower frequency are summed up to get HS, as the heart sound energy has low-frequency components. A total of 40 pairs of HS and LS signals are analyzed to estimate the efficiency of the algorithm. These signals are appropriated from online available resources. The signals are pre-processed and then decomposed by using HVD method. To reinforce the performance of the algorithm, the results were verified with an impartial panel of 2 doctors and calculated the correlation coefficient amongst the original HS signal and reconstructed HS signal.
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References
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