第23卷
9
2015年6月
文章编号1004-924X(2015)06-1580-07
光学精密工程
Optics and Precision Engineering
Vol.23No.6
Jun.2015
基于集合经验模态分解的人体结肠动力分析
鲁丽，颜国正，赵凯，许飞
（上海交通大学电子信息与电气工程学院，上海200240）
摘要：针对目前临床上应用的便秘诊断措施有创且诊断效果不理想的间题，开展了基于无创检测设备获得胃肠道生理信息的研究。利用非线性分析方法分析人体结肠动力并找出正常人和便秘病人之间的区别，为临床诊断便秘提供参考。对8个正常人和10个便秘病人的结肠压力数据进行了分析。首先，通过阅值和集合经验模态分解（EEMD)有效滤除了结肠压力数据中的呼吸，咳嗽，电磁干扰等噪声；然后，提取了表征结肠动力的特征参数如结肠收缩频率，动力指数，平均收缩波峰值；最后，通过：检验比较了正常人和便秘病人结肠特征参数。结果显示；正常人和便秘病人的收缩频率，动力指数有明显统计不同（p<0.05)，然而，正常人和便秘病人的平均收缩波峰值没有明显统计差别。分析表明，收缩频率、动力指数可以区分正常人和便秘病人。
关键调：无线胶衰；无线传感器慢传输型便秘；结励动力学；集合经验模态分解
中图分类号：TP242.3;R574.62
文献标识码：A
doi:10.3788/OPE, 20152306.1580
AnalysisofhumancolonicmotilityusingEEMD
LU Li',YAN Guo-zheng, ZHAO Kai, XU Fei(School of Electrical and Information Engineering,
ShanghaiJiao Tong University,Shanghai 200240,China)%Correspondingauthor,E-mail.luziaolio402@163.com
Abstract: As current diagnostic methods for constipation are invasive and the diagnostic effects are not ideal, this paper researches how to use the noninvasive detection equipment to obtain the gastrointestinal physiological information. The nonlinear analysis methods were taken to analyze human colon dynamics and to find out the difference between normal people and constipated patients, then to provide references for clinical diagnosis of the constipation, Colonic pressure data from 8 healthy and 1o constipated subjects were analyzed. Firstly, the breathing, coughing, electromagnetic interference noise in the colonic pressure data were filtered by thresholds and the Ensemble Empirical Mode Decomposition (EEMD). Then, the colonic contractile frequency, motility index and the average peak of peristaltic wave were extracted to characterize the colonic dynamic properties, Finally, the feature parameters between healthy and constipated subjects were compared by using the t test. Analysis shows that the number of contractions and the motility indexes of healthy subjects are different from that of the patients with constipation (p 收稿日期：2014-10-15；修订日期：2014-12-30
基金项目：国家自然科学基金资助项目（No.60875061，No.31170968，No.30800235)；载人航天领域预研基金资助项
目（No.010203）；上海市科委资助项目（No.09DZ1907400）