Abstract
The signal quality limits the applicability of phonocardiography at the patients’ domicile. This work proposes the signal-to-noise ratio of the recorded signal as its main quality metrics. Moreover, we define the minimum acceptable values of the signal-to-noise ratio that warrantee an accuracy of the derived parameters acceptable in clinics. We considered 25 original heart sounds recordings, which we corrupted by adding noise to decrease their signal-to-noise ratio. We found that a signal-to-noise ratio equal to or higher than 14 dB warrants an uncertainty of the estimate of the valve closure latencies below 1 ms. This accuracy is higher than that required by most clinical applications. We validated the proposed method against a public database, obtaining results comparable to those obtained on our sample population. In conclusion, we defined (a) the signal-to-noise ratio of the phonocardiographic signal as the preferred metric to evaluate its quality and (b) the minimum values of the signal-to-noise ratio required to obtain an uncertainty of the latency of heart sound components compatible with clinical applications. We believe these results are crucial for the development of home monitoring systems aimed at preventing acute episodes of heart failure and that can be safely operated by naïve users.
Highlights
Heart sounds are acoustic waves mainly generated by the closing of heart valves [1].Their noninvasive recording by means of a microphone gives origin to a biomedical signal known as phonocardiogram (PCG)
PCG analysis was proved as a valuable tool for the follow-up of patients affected by cardiovascular diseases (CVDs), the first world cause of death according to the
In a previous study [4], we presented an automated algorithm for the segmentation of heart sounds within a PCG recording and for the user independent measurement of the timing of heart sound components: mitral and tricuspid components in first heart sound (S1 ), and aortic and pulmonary components in second heart sound (S2 )
Summary
Heart sounds are acoustic waves mainly generated by the closing of heart valves [1]. Their noninvasive recording by means of a microphone gives origin to a biomedical signal known as phonocardiogram (PCG). PCG analysis was proved as a valuable tool for the follow-up of patients affected by cardiovascular diseases (CVDs), the first world cause of death according to the. In a previous study [4], we presented an automated algorithm for the segmentation of heart sounds within a PCG recording and for the user independent measurement of the timing of heart sound components: mitral and tricuspid components in first heart sound (S1 ), and aortic and pulmonary components in second heart sound (S2 ). The knowledge of the latency of heart sound components is helpful in studying the electromechanical coupling of the heart muscle fibers of a subject and a variety of pathologies, such as heart failure [4,5,6,7,8]
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