心肌缺血检测的实用系统开发

发布时间：2018-11-11 21:39

【摘要】：在当今世界,心血管疾病对人类的健康造成了巨大危害,引起了医疗卫生相关领域的广泛研究。许多心血管疾病均伴有心肌缺血,对心肌缺血的检测在临床上显得尤为重要。目前,根据心电图来判断心肌缺血是临床上的常用方法之一,然而,这种方法需要医务人员有丰富的临床经验才有可能做出正确判断。另外,心电图所反映出来的特征信息十分有限,病人心肌供血的实际情况与心电图所揭示的信息并非完全一致对应,这就使得临床上可能无法仅凭心电图就做出准确判断,往往需要其他医学手段的配合验证。本文介绍了一套心肌缺血检测系统,该系统可以挖掘心电信号所携带的丰富的动力学信息,并对其进行局部准确建模。根据该系统的建模结果——心电动力学图(Cardiodynamicsgram, CDG)的形态特点可以方便判断病人是否患有心肌缺血。CDG可以比较全面地反映病人的心肌供血情况,更有助于医务人员做出准确的判断。另外,根据本系统进行心肌缺血检测对操作者的要求相对来说较低。检测系统的算法基础是确定学习理论,该理论研究的是动态环境下的确定学习,通过该理论可以实现对未知动态环境下的知识进行获取、表达、存储和利用。对于一个系统状态为周期(回归)轨迹的连续(离散)非线性动态系统,确定学习理论可以利用径向基函数神经网络对此系统动态进行局部准确建模。心肌缺血检测系统是在MATLAB GUI的环境下开发的。系统主要包括心电信号数据采集、数据滤波、数据学习训练、心电图和心电向量图(VCG)以及CDG的三维显示、检测结果的显示等几项主要功能,并且该系统还可以实现对心电图、CDG和检测结果的打印。经过临床研究,检测系统可以初步实现判断心肌缺血。
[Abstract]:In today's world, cardiovascular disease has caused great harm to human health and caused extensive research in medical and health related fields. Many cardiovascular diseases are accompanied by myocardial ischemia, the detection of myocardial ischemia is particularly important in clinical. At present, it is one of the commonly used methods to judge myocardial ischemia according to electrocardiogram. However, this method requires medical staff to have rich clinical experience in order to make a correct judgment. In addition, the characteristic information reflected by electrocardiogram is very limited, and the actual situation of the patient's myocardial blood supply is not completely consistent with the information revealed by the electrocardiogram, which makes it possible to make an accurate judgment on the basis of electrocardiogram alone in clinic. It often needs other medical means to cooperate and verify. A myocardial ischemia detection system is introduced in this paper. The system can mine the rich dynamic information carried by ECG signal and model it locally accurately. According to the modeling result of the system, the morphologic characteristics of electrocardiogram (Cardiodynamicsgram, CDG) can be used to determine whether the patient has myocardial ischemia or not. CDG can reflect the myocardial blood supply of the patient comprehensively. It is more helpful for medical staff to make accurate judgment. In addition, the requirement of myocardial ischemia detection based on this system is relatively low. The algorithm of detection system is based on deterministic learning theory, which studies deterministic learning in dynamic environment. Through this theory, knowledge in unknown dynamic environment can be acquired, expressed, stored and utilized. For a continuous (discrete) nonlinear dynamic system in which the state of the system is periodic (regression) trajectory, the determination learning theory can use radial basis function neural network to model the dynamic state of the system. The myocardial ischemia detection system was developed in the context of MATLAB GUI. The system mainly includes ECG data acquisition, data filtering, data learning and training, electrocardiogram and ECG vector graph (VCG) and CDG 3D display, detection results display and other main functions. And the system can also achieve the electrocardiogram, CDG and test results print. After clinical study, the detection system can be used to judge myocardial ischemia.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：R542.2;TP274

【参考文献】