【摘要】：在當(dāng)今世界,心血管疾病對(duì)人類的健康造成了巨大危害,引起了醫(yī)療衛(wèi)生相關(guān)領(lǐng)域的廣泛研究。許多心血管疾病均伴有心肌缺血,對(duì)心肌缺血的檢測(cè)在臨床上顯得尤為重要。目前,根據(jù)心電圖來判斷心肌缺血是臨床上的常用方法之一,然而,這種方法需要醫(yī)務(wù)人員有豐富的臨床經(jīng)驗(yàn)才有可能做出正確判斷。另外,心電圖所反映出來的特征信息十分有限,病人心肌供血的實(shí)際情況與心電圖所揭示的信息并非完全一致對(duì)應(yīng),這就使得臨床上可能無法僅憑心電圖就做出準(zhǔn)確判斷,往往需要其他醫(yī)學(xué)手段的配合驗(yàn)證。本文介紹了一套心肌缺血檢測(cè)系統(tǒng),該系統(tǒng)可以挖掘心電信號(hào)所攜帶的豐富的動(dòng)力學(xué)信息,并對(duì)其進(jìn)行局部準(zhǔn)確建模。根據(jù)該系統(tǒng)的建模結(jié)果——心電動(dòng)力學(xué)圖(Cardiodynamicsgram, CDG)的形態(tài)特點(diǎn)可以方便判斷病人是否患有心肌缺血。CDG可以比較全面地反映病人的心肌供血情況,更有助于醫(yī)務(wù)人員做出準(zhǔn)確的判斷。另外,根據(jù)本系統(tǒng)進(jìn)行心肌缺血檢測(cè)對(duì)操作者的要求相對(duì)來說較低。檢測(cè)系統(tǒng)的算法基礎(chǔ)是確定學(xué)習(xí)理論,該理論研究的是動(dòng)態(tài)環(huán)境下的確定學(xué)習(xí),通過該理論可以實(shí)現(xiàn)對(duì)未知?jiǎng)討B(tài)環(huán)境下的知識(shí)進(jìn)行獲取、表達(dá)、存儲(chǔ)和利用。對(duì)于一個(gè)系統(tǒng)狀態(tài)為周期(回歸)軌跡的連續(xù)(離散)非線性動(dòng)態(tài)系統(tǒng),確定學(xué)習(xí)理論可以利用徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)對(duì)此系統(tǒng)動(dòng)態(tài)進(jìn)行局部準(zhǔn)確建模。心肌缺血檢測(cè)系統(tǒng)是在MATLAB GUI的環(huán)境下開發(fā)的。系統(tǒng)主要包括心電信號(hào)數(shù)據(jù)采集、數(shù)據(jù)濾波、數(shù)據(jù)學(xué)習(xí)訓(xùn)練、心電圖和心電向量圖(VCG)以及CDG的三維顯示、檢測(cè)結(jié)果的顯示等幾項(xiàng)主要功能,并且該系統(tǒng)還可以實(shí)現(xiàn)對(duì)心電圖、CDG和檢測(cè)結(jié)果的打印。經(jīng)過臨床研究,檢測(cè)系統(tǒng)可以初步實(shí)現(xiàn)判斷心肌缺血。
[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.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：R542.2;TP274

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