总体经验模态细分法提取血流超声多普勒信号的研究  

Extraction of Doppler Ultrasound Blood Signals Using the Delicate Separation Method Based on the EEMD Algorithm

作　　者：林文晶[1] 张榆锋[1] 章克信[2] 李支尧[2] 李海燕[1] 高莲[1] 李媛媛[1] 

机构地区：[1]云南大学信息学院电子工程系,云南昆明650091 [2]昆明医学院第二附属医院,云南昆明650031

出　　处：《电子学报》2014年第7期1424-1428,共5页Acta Electronica Sinica

基　　金：国家自然科学基金(No.61261007);云南省自然科学基金重点项目(No.2013FA008)

摘　　要：提出基于总体经验模态分解(EEMD)血流细分法提高血流超声多普勒信号提取精度.首先估计辅助分析所需的白噪声幅度,进而用EEMD得到无模态混叠的本征模态函数(IMF)组,最后分离出血流信号的IMF.将本方法应用于计算机仿真和人体实测超声多普勒信号,并与高通滤波器法、原EMD法和EMD细分法比较.结果表明本文方法,提取的血流信号精度最高,特别对WBSR=70dB的混合信号,其精度比上述方法分别提高35%、38%及17%.A fine separation based on the ensemble empirical mode decomposition （EEMD） algorithm is proposed to im- prove the accuracy of the blood flow signal extraction. Firstly, a white noise with proper amphtude is estimated according to the en- ergy of blood flow signals.Intrinsic mode functions （IMFs） without mode mixing are obtained by EEMD. Finally, those IMFs be- long to the blood flow are delicately separated. Experimental results from both simulation and real human carotid Doppler signals based on the proposed method are compared with those by using the high pass filter, the original empirical mode decomposition （EMD） method and the improved EMD delicate separation method. It is shown that the proposed method provides the highest sepa- ration accuracy. Especially for those signals with larger WBSR = 70dB, the accuracy is higher than those based on the methods men- tioned above by 35% ,38% and 17% ,respectively.

关 键 词：血流超声信号 血管壁搏动信号 信号提取 总体经验模态分解 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]