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一般地,心电图(ECG)信号取样速率为200次/秒或更高,从而产生了大量的数据,这就对存储、分析以及传送造成了困难。在实时操作中,数据缩减算法可在不丢失临床诊断信息成份的情况下对数据量进行缩减。但也必须为ECG信号的分析留有足够的计算时间。这里,我们介绍一种适于这样的实时应用的,叫做CORTES的新的算法。这个算法把叫做TP和AZTEC的另外两个技术的最好的特点结合了起来。我们给出的一个研究结果找到了控制CORTES算法中变量的最佳实验值。我们对多种编码
In general, ECG signal sampling rates of 200 beats / second or higher result in a large amount of data, making it difficult to store, analyze and transmit. In real-time operations, data reduction algorithms reduce the amount of data without losing the components of clinical diagnostic information. However, enough time must be left for the ECG signal analysis. Here, we introduce a new algorithm called CORTES that is suitable for such real-time applications. This algorithm combines the best features of the other two technologies, called TP and AZTEC. One of our findings finds the best experimental value for controlling variables in the CORTES algorithm. We have a variety of coding