Wavelet transforms in the analysis of mechanical heart valve cavitation

Luke H. Herbertson, Varun Reddy, Keefe B. Manning, Joseph P. Welz, Arnold Anthony Fontaine, Steven Deutsch

Research output: Contribution to journalArticle

12 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)217-222
Number of pages6
JournalJournal of Biomechanical Engineering
Volume128
Issue number2
DOIs
StatePublished - Apr 1 2006

Fingerprint

Wavelet Analysis
Heart Valves
Cavitation
Wavelet transforms
Cerebrovascular Circulation
Signal-To-Noise Ratio
Embolism
Acoustics
Noise
Gases
Stroke
Acoustic waves
Water
Hydrophones
Acoustic noise
Signal to noise ratio
Blood

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Physiology (medical)

Cite this

Herbertson, Luke H. ; Reddy, Varun ; Manning, Keefe B. ; Welz, Joseph P. ; Fontaine, Arnold Anthony ; Deutsch, Steven. / Wavelet transforms in the analysis of mechanical heart valve cavitation. In: Journal of Biomechanical Engineering. 2006 ; Vol. 128, No. 2. pp. 217-222.
@article{77527da33dc34e94aff2b6520a9031eb,
title = "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.",
author = "Herbertson, {Luke H.} and Varun Reddy and Manning, {Keefe B.} and Welz, {Joseph P.} and Fontaine, {Arnold Anthony} and Steven Deutsch",
year = "2006",
month = "4",
day = "1",
doi = "10.1115/1.2165694",
language = "English (US)",
volume = "128",
pages = "217--222",
journal = "Journal of Biomechanical Engineering",
issn = "0148-0731",
publisher = "American Society of Mechanical Engineers(ASME)",
number = "2",

}

Wavelet transforms in the analysis of mechanical heart valve cavitation. / Herbertson, Luke H.; Reddy, Varun; Manning, Keefe B.; Welz, Joseph P.; Fontaine, Arnold Anthony; Deutsch, Steven.

In: Journal of Biomechanical Engineering, Vol. 128, No. 2, 01.04.2006, p. 217-222.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Wavelet transforms in the analysis of mechanical heart valve cavitation

AU - Herbertson, Luke H.

AU - Reddy, Varun

AU - Manning, Keefe B.

AU - Welz, Joseph P.

AU - Fontaine, Arnold Anthony

AU - Deutsch, Steven

PY - 2006/4/1

Y1 - 2006/4/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=33645973702&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33645973702&partnerID=8YFLogxK

U2 - 10.1115/1.2165694

DO - 10.1115/1.2165694

M3 - Article

C2 - 16524333

AN - SCOPUS:33645973702

VL - 128

SP - 217

EP - 222

JO - Journal of Biomechanical Engineering

JF - Journal of Biomechanical Engineering

SN - 0148-0731

IS - 2

ER -