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Improvements of the power spectrum based on Hilbert-Huang extract pulsatile displacement of the vessel wall

Author: ChenQiuYing
Tutor: ZhangYuFeng
School: Yunnan University
Course: Signal and Information Processing
Keywords: Empirical Mode Decomposition End effect Cycle extension method Modal aliasing Overall average empirical mode decomposition Hilbert spectrum The pulsatility speed of the vessel wall The pulsatility displacement of the vessel wall
CLC: TN911.7
Type: Master's thesis
Year: 2010
Downloads: 43
Quote: 0
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Abstract


Cardiovascular disease is a disease of the heart, brain and blood vessels, and its incidence, morbidity and mortality is high. The study found that the elasticity of the arterial wall anomaly detection has an extremely important role in the pathogenesis of the cardiovascular system reveals. Latest proposed for the detection of vascular wall pulsatile displacement method is based on the traditional EMD algorithm of continuous ultrasound Doppler signal detection, it can automatically separate the ultrasound Doppler mixed-signal, pulsatility signal Hilbert spectrum, thus from Hilbert spectrum pulsating displacement of the vessel wall. The method has the advantages of simple algorithm, and a small amount of data processing, computation time is short and fast, has a certain practicality and feasibility. But the traditional EMD algorithm endpoint effect and mode mixing two larger problems, these two issues will cause the vessel wall pulsatility Hilbert spectral distortion, or even lose its original physical meaning, resulting in the method pulsating displacement signals extracted out of the vessel wall there are large errors. This paper presents a EMD_PE algorithm to suppress the traditional EMD algorithm endpoint effect, and based on the noise assisted analysis EEMD algorithm to eliminate the traditional EMD algorithm modal aliasing to improve the vessel wall pulsatility Hilbert spectrum signal, and thus more accurately extract pulsatile displacement signal of the blood vessel wall. In order to verify the effectiveness of the two detection methods, the paper carried out a computer simulation. In the simulation experiments, first of all, Fish blood flow simulation model of a the 50 quadrature demodulator bidirectional ultrasound Doppler mixed signal simulation on the computer; then were used to EMD_PE algorithm and EEMD algorithm after the direction of separation decomposed into a set of intrinsic mode function before and after the ultrasound Doppler signal, and the signal power than the intrinsic mode function belongs pulsatility signal extracted; Finally, the extracted intrinsic mode function Hilbert transform of the vessel wall pulsatility Hilbert spectrum of the signal, and then extracted from the Hilbert Spectrum pulsation of the vascular wall the maximum speed curve and the maximum displacement curve, and the value obtained with continuous ultrasound Doppler signal detection method based on the conventional EMD algorithm is compared. With pulsatile displacement detection method based the EEMD algorithm and EMD_PE algorithm to extract the vessel wall with the theoretical value error between the mean and standard deviations were 4.2 ± 0.6um and 7.8 ± 1.4um, than traditional EMD algorithm-based detection methods value of 16.2 ± 3.2um many small, these results suggest that this thesis improved detection method is effective to extract the pulsating displacement of the vessel wall, and improved accuracy. Pulsatile displacement of the vessel wall of these blood vessels flexible access to information will contribute to the early diagnosis and prevention of cardiovascular and cerebrovascular diseases.

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