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A novel algorithm for sudden cardiac death risk estimation using Lab VIEW

机译:利用Lab VIEW估算心脏猝死风险的新算法

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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:快速评估心脏异常的需求不可低估。心脏猝死(SCD)是一种此类疾病,因为它是致命的,并且是导致心血管疾病死亡的主要原因,因此需要立即予以关注。大多数心血管畸变归因于心律不规则,导致异常PQRST值,该值可从患者的ECG追踪到。 ECG是一种简单的非侵入性测试,可记录心脏的电活动。这用于检测和定位严重心脏问题(例如SCD)的来源。该项目旨在开发新颖的算法,以使用ECG分析评估心脏性猝死的风险。所开发的算法使用在同一数据库上评估的不同算法来提高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。拟议的系统集成了两个独立的模块:SCD检测和SCD预测。由于信号会受到各种伪像和噪声的影响,因此,使用快速傅里叶变换(FFT)进行ECG信号的预处理。然后进行异常检测。该实现使用Lab VIEW完成,Lab VIEW是用于实时系统设计仿真和虚拟仪器的通用图形编程工具。在为SCD检测制定了可靠的算法和可靠的解决方案之后,将把工作扩展到以合理的精度预测SCD。

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