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An integrated intelligent computing method for the detection and interpretation of ECG based cardiac diseases

机译:用于检测和解释基于ECG的心脏病的集成智能计算方法

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摘要

Intelligent computing system and knowledge-based system have been widely used in the diagnosis and classification of ECG based diseases. Several detection methods of ECG parameters for a particular disease have also been reported in the literature. But little effort has been made by researchers to combine both. In this work, an integrated model of rule base system for generating cases and ANN methods for matching cases in the case base reasoning model for the interpretation and diagnosis of sinus disturbances (SD) is developed. The SD is hierarchically structured in terms of their physio-psycho parameters and ECG based parameters. Cumulative confidence factor (CCF) is computed at different nodes of hierarchy. The SD considered are sinus arrest, sinus bradycardia, sinus tachycardia and sinus arrhythmia. MIT/BIH ECG database is used in the simulation study. The basic objective of this work is to enhance the computational effort with certain level of efficiency and accuracy.
机译:智能计算系统和基于知识的系统已广泛用于基于ECG的疾病的诊断和分类。文献中还报道了几种针对特定疾病的ECG参数检测方法。但是研究人员几乎没有做出任何努力来将两者结合起来。在这项工作中,开发了一个用于生成案例的规则库系统和用于匹配案例的ANN方法的集成模型,用于解释和诊断窦性疾病(SD)的案例库推理模型中。 SD是根据其生理心理参数和基于ECG的参数进行分层构造的。在层次结构的不同节点上计算累积置信度(CCF)。所考虑的SD是窦性心律停止,窦性心动过缓,窦性心动过速和窦性心律不齐。 MIT / BIH ECG数据库用于仿真研究。这项工作的基本目标是以一定水平的效率和准确性来增强计算工作量。

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