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据估计,15～30%的怀疑或确诊患冠状动脉疾病的病人由于各种各样的原因如肥胖、体质虚弱、跛足等,不能完成足量的运动紧张试验。食道前房诱导为不能剧烈运动的病人提供了另一种诱发心肌紧张的无创方法。尽管计算机分析在传统的运动紧张试验中普遍用以进行心电图分析,食道前房诱导期记录的表面ECG信号受大的伪差干扰而使标准的计算机软件无法识别伪差与QRS波群。本文描述了一种实用的信号处理方法来识别在上述过程中产生的表面ECG信号。该算法采用新颖的线性和非线性变换系统,能够在伪差相似或附
It is estimated that 15-30% of patients suspected or diagnosed with coronary artery disease are unable to complete sufficient exercise stress tests for a variety of reasons such as obesity, frailty, lameness and the like. Anterior chamber esophageal induction of non-strenuous exercise provides another noninvasive method of myocardial tension. Although computer analysis is commonly used in traditional exercise stress tests for electrocardiographic analysis, surface ECG signals recorded during the esophageal anterior chamber induction period suffer from large artifacts that make standard computer software unidentifiable artifacts and QRS complexes. This article describes a practical signal processing method to identify surface ECG signals generated in the above process. The algorithm uses novel linear and non-linear transform system, which can be similar in pseudo-difference or attached