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A Novel Algorithm for Sudden Cardiac Death Risk Estimation Using Lab VIEW

机译:一种使用实验室视图突然心脏死亡风险估算的新算法

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The need for quick diagnosis of cardiac abnormalities cannot be underestimated. Sudden cardiac death (SCD) is one such disease that needs immediate attention as it is fatal and is a leading cause of cardiovascular mortality. Most of the cardiovascular aberrations are due to irregular heart rhythm resulting in abnormal PQRST values which can be traced from the patient's ECG. ECG is a simple, non-invasive test that records the heart's electrical activity. This is used to detect and locate the sources of severe heart problems such as SCD. This project is aimed at developing novel algorithms to estimate the risk of sudden cardiac death using ECG analysis. The developed algorithms improve the best results reported in other papers using different algorithms evaluated on the same database[1]. ECG signals from MIT BIH database are used to validate the algorithm. The proposed system integrates two separate modules: SCD detection and SCD prediction. The preprocessing of ECG signals is done using Fast Fourier Transform (FFT) as the first step since the signals are subjected to various artifacts and noise. Then the detection of the abnormalities is taken up. The implementation is done using Lab VIEW which is a versatile graphical programming tool for real-time systems design simulation and virtual instrumentation. After having formulated a robust algorithm and a reliable solution for SCD detection the work will be extended towards predicting SCD with reasonable accuracy.
机译:对心脏异常的快速诊断的需求不能低估。突发的心脏死亡(SCD)是一种这种疾病,需要立即关注它是致命的,并且是心血管死亡率的主要原因。大多数心血管像差是由于心律不规则导致的PQRST值异常,其可以从患者的ECG追踪。 ECG是一种简单,无侵入性的测试,记录了心脏的电气活动。这用于检测和定位诸如SCD之类的严重心脏问题的来源。该项目旨在开发新的算法来估算使用心电图分析突然心死的风险。发达的算法在同一数据库中评估的不同算法提高了其他论文中报告的最佳结果[1]。来自MIT BIH数据库的ECG信号用于验证算法。所提出的系统集成了两个单独的模块:SCD检测和SCD预测。由于该信号经受各种伪像和噪声,因此使用快速傅里叶变换(FFT)来完成ECG信号的预处理。然后占据异常的检测。该实现是使用实验室视图完成的,该实验室视图是一种用于实时系统设计仿真和虚拟仪器的多功能图形编程工具。在制定了强大的算法和SCD检测的可靠解决方案之后,该工作将以合理的准确度预测SCD。

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