基于概率密度函数的房颤检测PPG信号提取算法研究。

Q3 Medicine
Open Biomedical Engineering Journal Pub Date : 2015-08-31 eCollection Date: 2015-01-01 DOI:10.2174/1874120701509010179
Kang Liang, Ying Sun, Fuying Tian, Shenghua Ye
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引用次数: 3

摘要

提出了一种基于概率密度函数(PDF)和相空间图法的光体积脉搏波信号提取方法。在论文中,PPG信息是通过智能手机从人的指尖生成的。然后利用相空间图算法将脉冲周期分离并重构为概率密度函数(PDF)。最后通过PDF的偏度发现正常窦性心律(NSR)与心房颤动(AF)的区别。本研究的结果表明,新方法在智能手机上检测AF是非常可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Research on Algorithm of Extracting PPG Signal for Detecting Atrial Fibrillation based on Probability Density Function.

Research on Algorithm of Extracting PPG Signal for Detecting Atrial Fibrillation based on Probability Density Function.

Research on Algorithm of Extracting PPG Signal for Detecting Atrial Fibrillation based on Probability Density Function.

Research on Algorithm of Extracting PPG Signal for Detecting Atrial Fibrillation based on Probability Density Function.

The paper introduced a new method based on probability density function (PDF) and phase space diagram method for photoplethysmography (PPG) signal extracting. In the paper, PPG information was generated from human fingertips by smartphones. The pulse wave period was then separated and reconstructed into probability density function (PDF) by the phase space diagram algorithm. The difference between normal sinus rhythm (NSR) and atrial fibrillation (AF) was finally found by skewness of the PDF. The results of the present study demonstrates that the new method is vividly viable for detecting AF on the smartphone.

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来源期刊
Open Biomedical Engineering Journal
Open Biomedical Engineering Journal Medicine-Medicine (miscellaneous)
CiteScore
1.60
自引率
0.00%
发文量
4
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