Study of HRV Dynamics and Comparison Using Wavelet Analysis and Pan Tompkins Algorithm

机译：基于小波分析和Pan Tompkins算法的HRV动力学研究和比较

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Heart rate variability (HRV) provides a non-invasive means of quantifying cardiac autonomic activity. It has been shown to be a powerful predictor of arrhythmia related complications in patients surviving the acute phase of myocardial infarction. It has also increasingly been used to measure autonomic nervous system activities. This work aims to study heart rate variability during normal or abnormal functioning of the heart and whether it can be used to predict the occurrence of any abnormality. Additionally, it aims to compare results based on wavelet analysis and Pan Tompkins algorithm. Both time domain analysis and frequency domain analysis of HRV are presented. The HRV dynamics is evaluated using non-parametric (Fast Fourier Transform) method. Results of stimulations in MATLAB are presented.

机译：心率变异性（HRV）提供了一种量化心脏自主神经活动的非侵入性手段。它已被证明是存活于心肌梗塞急性期的患者中与心律不齐相关的并发症的有力预测指标。它也越来越多地用于测量自主神经系统活动。这项工作旨在研究心脏正常或异常功能期间的心率变异性，以及是否可用于预测任何异常的发生。此外，它旨在比较基于小波分析和Pan Tompkins算法的结果。提出了HRV的时域分析和频域分析。使用非参数（快速傅立叶变换）方法评估HRV动力学。给出了MATLAB中的激励结果。

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来源
《2012 ASE International Conference on BioMedical Computing》|2012年|43-49|共7页
会议地点 Washington DC(US);Washington DC(US)
作者
Goyal Yamini; Jain Anshul;
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原文格式 PDF
正文语种 eng
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关键词
Daubechies Wavelets; Electrocardiogram; Event Detection; Fast Fourier Transform; Heart Rate Variability; Pan Tompkins Algorithm;

机译：Daubechies小波；心电图；事件检测；快速傅立叶变换；心率变异性；潘汤普金斯算法；;

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Study of HRV Dynamics and Comparison Using Wavelet Analysis and Pan Tompkins Algorithm

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