利用小波变换提取和分析心动周期信号中子信号  

Extracting and analyzing sub-signals in heart period signal by using wavelet transform

作　　者：李章勇[1] 刘圣蓉[1] 谢正祥[2] 

机构地区：[1]重庆邮电学院,重庆400065 [2]重庆医科大学生物医学工程研究室,重庆400016

出　　处：《重庆邮电学院学报（自然科学版）》2006年第1期130-133,共4页Journal of Chongqing University of Posts and Telecommunications(Natural Sciences Edition)

基　　金：国家自然科学基金资助项目(60471041);重庆邮电学院科研基金资助项目(A2004-61)

摘　　要：为了采用小波变换提取心动周期信号(HPS)中的子信号,而分别对自愿受试者10名从卧位和站立体位采集心电信号,小波变换分解心动周期信号为一个细节成份和一个近似成份。对HPS、近似成份和细节成份都进行快速傅立叶变换,计算出了功率参数。心动周期信号的总功率从卧位到站位有显著的变化,近似成份的功率显著增加,细节成份的功率变化不明显,细节占总功率的比值显著变化。比较这两个体位的结果,其近似成份可能代表了交感神经系统的活动,而细节成份表达了副交感神经系统的调节。交感和副交感神经系统功能可分别由小波变换分解的2组成份的数字和图形参数作定量解释。To extract sub-signal of heart period signal （HPS）, an important signal processing approach, called wavelet transform （WT） was adapted. Electrocardio signal （ECS） was obtained from ten volunteers. Wavelet Transform decomposed HPS into one detailed level and one approximation. HPS approximation and detail were transformed by fast Fourier transformation （FFT）. Power indexes were calculated. The total power of HPS varied and the power of approximation was significantly increased, but that of detail had no clear change and the ratio of approximation to total power also was increased significantly in the patient from lying to standing. Compared with the two postural results, it shows that approximation signal may express sympathetic activity, and detail signal represents parasympathetic modification. Sympathetic and parasympathetic nervous function can be evaluated respectively and quantificationally by data and graphs from the two decomposed components by wavelet transform.

关 键 词：小波变换 自主神经系统 心动周期信号 心电信号 

分 类 号：R540.4[医药卫生—心血管疾病] O174.21[医药卫生—内科学]