Wavelet transforms in the analysis of mechanical heart valve cavitation.
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.