Wavelet Transforms in the Analysis of Mechanical Heart Valve Cavitation

Abstract

Cavitation is known to cause blood element damage and may introduce gaseous emboli into the cerebral circulation, increasing the patient's risk of stroke. Discovering methods to reduce the intensity of cavitation induced by mechanical heart valves (MHVs) has long been an area of interest. A novel approach for analyzing MHV cavitation is presented. A wavelet denoising method is explored because currently used analytical techniques fail to suitably unmask the cavitation signal from other valve closing sounds and noise detected with a hydrophone. Wavelet functions are used to denoise the cavitation signal during MHV closure and rebound. The wavelet technique is applied to the signal produced by closure of a 29-mm Medtronic-Hall MHV in degassed water with a gas content of 5 ppm. Valve closing dynamics are investigated under loading conditions of 500, 2500, and 4500 mm Hg/s. The results display a marked improvement in the quantity and quality of information that can be extracted from acoustic cavitation signals using the wavelet technique compared to conventional analytical techniques. Time and frequency data indicate the likelihood and characteristics of cavitation formation under specified conditions. Using this wavelet technique we observe an improved signal-to-noise ratio, an enhanced time-dependent aspect, and the potential to minimize valve closing sounds, which disguise individual cavitation events. The overall goal of this work is to eventually link specific valves with characteristic waveforms or distinct types of cavitation, thus promoting improved valve designs.

A Novel Study of Mechanical Heart Valve Cavitation in a Pressurized Pulsatile Duplicator

“…Therefore, it will be difficult to separate the two sounds by applying filters or using other modern signal processing techniques. 32 The aim of this study was not to physically separate the two sounds but to compare the spectral characteristics of the sound signals collected near an MHV (potentially containing both mechanical closing sound and cavitation noise) with those of the mechanical closing sound alone.…”

Enhancement of signal processing technique for quantification of non-deterministic events of pathological heart signals using wavelet transform

“…For quantification of cavitation, a few methods were proposed to remove this component from the signal and to quantify the level of cavitation by Garrison et al [11], Johansen et al [12,13], Sohn et al [14] and Herbertson et al [15]. In this paper the method used is the Johansen algorithm proposed by Johansen [4] where in the modification is made at two levels: one at the segmentation algorithm where the wavelet family is applied and analysed for the result.…”

Wavelet analysis techniques in cavitating flows

“…The use of the CWT in the analysis of cavitating and bubbly flows has found broad application from classical cloud shedding physics [21][22][23], cavitation noise spectra [24,25], biomedical applications such as cavitation in mechanical heart valves [26], through to microbubble size measurement [27] and complex bubble dynamic behaviour [28,29]. Shedding cavitation may involve coherence with multiple frequencies present and frequency varying with flow conditions.…”