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Application of extension method and chaos theory in ECG identity recognition system

机译:扩展方法和混沌理论在心电识别系统中的应用

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An ECG process based on Einthoven principle was developed for this study. A circuit and DAQ card were incorporated in a human machine interface using LabVIEW to detect the PQRSTpoints in ECG and display the processed ECG signals of the test subjects. The ECG data saved were plotted into dynamical map of chaotic dynamic error using a master-slave chaos system. Chaos eye was selected as the feature and an identity database was built using an element model. Personal identity was identified by categorizing with extension method. Finally, the design was tested on 35 subjects to yield 94.3% of positive identification rate. The results suggested that the identity identification method developed in this study features quick identification, high positive identification rate and good reliability.
机译:为这项研究开发了基于Einthoven原理的心电图过程。使用LabVIEW将电路和DAQ卡集成到人机界面中,以检测ECG中的PQRST点并显示测试对象的已处理ECG信号。使用主从混沌系统将保存的ECG数据绘制到混沌动态误差的动态图中。选择了混沌眼睛作为特征,并使用元素模型构建了身份数据库。通过扩展方法分类来识别个人身份。最后,该设计在35位受试者上进行了测试,产生了94.3%的阳性识别率。结果表明,本研究开发的身份识别方法具有识别速度快,阳性识别率高,可靠性高的特点。

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