Ensemble Empirical Mode Decomposition Applied for PPG Motion Artifact

被引：0

作者：

Sadrawi, Muammar ^{[1
]}

Shieh, Jiann-Shing ^{[1
]}

Haraikawa, Koichi ^{[2
]}

Chien, Jen Chien ^{[2
]}

Lin, Chien Hung ^{[3
]}

Abbod, Maysam F. ^{[4
]}

机构：

[1] Yuan Ze Univ, Ctr Big Data & Digital Convergence, Dept Mech Engn & Innovat, Chungli, Taiwan

[2] Kinpo Elect Inc, Hlth & Beauty Res Ctr, New Taipei, Taiwan

[3] Cal Comp Inc, Hlth & Beauty Res Ctr, New Taipei, Taiwan

[4] Brunel Univ London, Dept Elect & Comp Engn, Uxbridge, Middx, England

来源：

2016 IEEE EMBS CONFERENCE ON BIOMEDICAL ENGINEERING AND SCIENCES (IECBES) | 2016年

关键词：

SPECTRUM;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This study evaluates the performance of the ensemble empirical mode decomposition (EEMD) filtering applied to the vertical movement motion artifact (MA). The evaluation of the filtering algorithm is investigated by the heart rate (HR) frequency assessment calculated by the fast Fourier transform (FFT), the intrinsic mode function (IMF) selection algorithm, and the periodogram. In this study, the results show that the raw photoplethysmograph (PPG) signal has some defects where the MA is applied, about 0.6 Hz of the vertical movement. Another result by utilizing the EEMD filter, it can be seen that, even though the period when the MA is activated, the HR frequency is relatively stable, about 1.3 Hz, by evaluating the time-frequency and maximum dominant frequency for a small period of the windowed signal.

引用

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页码：266 / 269

页数：4

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