본문 바로가기
KERD
논문KCI 등재

Study on the Diagnosis of Abnormal Prosthetic Valve

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

The two major problems related to the blood flow in replaced prosthetic heart valve are thrombus formation and hemolysis. Reliability of prosthetic valve is very important because its failure means the death of patient. There are many factors affecting the valvular failures and their representatives are mechanical failure and thrombosis, so early noninvasive detection is essentially required. The purpose of this study is to detect the various thromboses formation by using acoustic signal acquisition and its spectral analysis on the frequency domain. We made the thrombosis models using Polydimethylsiloxane (PDMS) and they are thrombosis model on the disc, around the sewing ring and fibrous tissue growth across the orifice of valve. Using microphone and amplifier, we measured the acoustic signal from the prosthetic valve, which is attached to the pulsatile mock circulation system. A/D converter sampled the acoustic signal and the spectral analysis is the main algorithm for obtaining spectrum. Then the spectrum of normal and 5 different kinds of abnormal valve were obtained. Each spectrum waveform shows a primary and secondary peak. The secondary peak changes according to the thrombus model. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. Acoustic measurement has been used as a noninvasive diagnostic tool and is thought to be a good method for detecting possible mechanical failure or thrombus.

Abstract

The two major problems related to the blood flow in replaced prosthetic heart valve are thrombus formation and hemolysis. Reliability of prosthetic valve is very important because its failure means the death of patient. There are many factors affecting the valvular failures and their representatives are mechanical failure and thrombosis, so early noninvasive detection is essentially required. The purpose of this study is to detect the various thromboses formation by using acoustic signal acquisition and its spectral analysis on the frequency domain. We made the thrombosis models using Polydimethylsiloxane (PDMS) and they are thrombosis model on the disc, around the sewing ring and fibrous tissue growth across the orifice of valve. Using microphone and amplifier, we measured the acoustic signal from the prosthetic valve, which is attached to the pulsatile mock circulation system. A/D converter sampled the acoustic signal and the spectral analysis is the main algorithm for obtaining spectrum. Then the spectrum of normal and 5 different kinds of abnormal valve were obtained. Each spectrum waveform shows a primary and secondary peak. The secondary peak changes according to the thrombus model. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. Acoustic measurement has been used as a noninvasive diagnostic tool and is thought to be a good method for detecting possible mechanical failure or thrombus.

참고문헌 (10)

  1. Foale RA, "Detection of aortic porcine valve dysfunction by maximum entropy spectral analysis", Circulation, 68, pp.42~49 (1983)
  2. Durand LG, "Evaluation of FFT-based and modern parametric methods for the spectral analysis of bioprosthetic valve sounds", IEEE Trans Biomedical Eng BME, 33, pp.572~578 (1986)
  3. Henry Edmunds L Jr., "Thromboembolic complications of current cardiac valvular prostheses", The Annals of Thoracic Surgery, 34, pp.96~106 (1981)
  4. Lee SH, "Performance evaluation of implantable artificial organs by sound spectrum analysis", ASAIO Journal, 40, pp.762~766 (1994)
  5. Kim HC, "Noninvasive diagnosis of mechanical failure of the implanted total artificial heart using neural network analysis of acoustic signal", ASAIO Jounal, 41, pp.271~276 (1995)
  6. Candy JV, "Classification of prosthetic heart valve sound", J Acoustic Soc Am, 97, pp.3675~3687 (1995)
  7. Reynolds Karen J, "Detection of mechanical changes to prosthetic heart valves by spectral analysis of valve closing sounds", J Acoust Soc Am, 98, pp.60~68 (1995)
  8. Chon KH, "Linear and nonlinear ARMA model parameter estimation using an artificial neural network", IEEE BME, 44, pp.168~174 (1997)
  9. 이환성, "기계식 인공 판막 주위의 유연성 구조가 표면 괴식에 미치는 영향", 의공학회지, 23(4), pp.309~315 (2002), 대한의용생체공학회
  10. 이혁수, "기계식 인공판막 상태 평가를 위한 컴퓨터 보조진단 시스템", 의공학회지, 25(5), pp.13~13 (2004), 대한의용생체공학회

관련 논문AI추천

이 간행물의 다른 논문 (10건)