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Enhancement of the heart sound envelope using the logistic function amplitude moderation method

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Abstract

This paper presents a new method to extract the envelope of the fundamental heart sound (S1 and S2) using the logistic function. The sigmoid characteristic of the logistic function is incorporated to segregate S1, and S2 signal intensities from silent or noise interfered systolic and diastolic intervals in a heart sound cycle. This signal intensity transformation brings uniformity to the envelope peak of S1 and S2 sound by inclining the transform intensity distribution towards the upper asymptote of the sigmoid curve. The proposed logistic function based amplitude moderation (LFAM) envelogram method involves finding the critical upper amplitude (xuc) above which the signals will be categorized as loud sound and the critical lower amplitude (xlc) below which the signal will be considered as noise. These critical values are regressively obtained from the signal itself by histogram analysis of intensity distribution. The performance is evaluated on noisy PCG dataset taken from PhysioNet/Computing in Cardiology Challenge 2016. The LFAM envelope yields better hill-valley discrimination of heart sounds from its silent/noisy signal intervals. The enhance heart sound envelope peaks are better than conventional methods. The proposed envelope feature is evaluated for heart sound segmentation using HSMM. There is a significant improvement in segmentation accuracy, especially at a low signal-to-noise ratio. The best average F1 score is 97.73%.

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... The enveloped based heart sound extraction is another form of application that has been recently used in (Kamson, Sharma, & Dandapat, 2020). The sigmoid characteristics of the logistic function is adopted by (Kamson et al., 2020), to separate the S1 and S2 heart sounds along with some silent or noise interfered systolic and diastolic intervals. ...
... The enveloped based heart sound extraction is another form of application that has been recently used in (Kamson, Sharma, & Dandapat, 2020). The sigmoid characteristics of the logistic function is adopted by (Kamson et al., 2020), to separate the S1 and S2 heart sounds along with some silent or noise interfered systolic and diastolic intervals. This method is named as logistic function based amplitude moderation (LFAM) envelogram method, which considers the amplitudes of the enveloped signals to identify and extract the information of fundamental heart sounds and systolic/diastolic intervals. ...
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This paper discusses four heart sound segmentation (HSS) methods: Wavelet transform, Fractal decomposition, Hilbert Transform, and Shannon Energy Envelogram, in order to identify the different cardiac sounds. Many research studies related to heart signal analysis, have adopted these methods to give high heart sound segmentation results, especially, for the identification of first and second heart sounds and murmurs. Performance of the heart sound segmentation results have also been compared with one other to identify the most efficient method(s), and it has been found that Shannon energy envelogram provides the best accuracies among the segmentation methods. Understandings of the segmentation methods for heart sound may pave the way for more advanced studies in other heart-related researches, including heart sound classifications.
... where x i is the value of the ith independent variable [32]. ...
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