模糊推理在基于心电图ST-T的心肌缺血判别中的应用

心电图(ECG)作为检测心肌缺血的一种方便、经济、无创的工具,其临床表现主要为ST-T段改变。由于心肌缺血很多情况下是瞬时发生,并且是无症状的,此时医务人员往往无法预料而不能及时采取干预措施,若能实现计算机的自动实时监控和及时预警,在心脏疾病诊断中具有重要的意义。本文融合目前比较公认的定量判断指标,主要包括:ST段偏移量、T波峰点幅值、ST/HR值,且在医务人员的协助指导下,应用模糊推理对心肌缺血进行了判别,经MIT-BIH数据库和公共数据库(LTST)中心电数据的验证,其敏感性和阳性预测值分别达到75%和78%,特异性和阴性预测值分别达到85%和87%。该方法更接近人的思维和认识,易于临床检测和工程实现。

Application of fuzzy reasoning to myocardial ischemia judgment based on electrocardiogram ST-T complex

Electrocardiogram (ECG) is a convenient, economic, and non-invasive detecting tool in myocardial ischemia (MI). Its clinical appearance is mainly exhibited by ST-T complex change. MI events are usually instantaneous and asymptomatic in some cases, which cannot be forecasted to have a precautionary measure in time by doctors. The automatic detection of MI by computer and a cued warning of danger in real time play an important role in diagnosing heart disease. With the help of the medical staff, some quantitative approbatory indicators, such as ST-segment deviation, the amplitude of T-wave peak and the rate of ST and heart rate (HR), were combined to judge MI using fuzzy reasoning. After MIT-BIH database and the long-term ST database (LTST) verification, sensitivity and positive predictive values reached 75% and 78% respectively, and specificity and negative predictive values were 85% and 87% respectively. In addition, the proposed method was close to human way of thinking and understanding, and easy to apply in clinical detection and engineering fields.