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

下载

页码：266 / 269

页数：4

共 50 条

[31] Automatic Motion and Noise Artifact Detection in Holter ECG Data Using Empirical Mode Decomposition and Statistical Approaches
Lee, Jinseok
McManus, David D.
Merchant, Sneh
Chon, Ki H.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2012, 59 (06) : 1499 - 1506
[32] Selection of Empirical Mode Decomposition Techniques for Extracting Breathing Rate From PPG
Motin, Mohammod Abdul
Karmakar, Chandan Kumar
Palaniswami, Marimuthu
IEEE SIGNAL PROCESSING LETTERS, 2019, 26 (04) : 592 - 596
[33] An effective electrocardiogram segments denoising method combined with ensemble empirical mode decomposition, empirical mode decomposition, and wavelet packet
Yue, Yaru
Chen, Chengdong
Wu, Xiaoyuan
Zhou, Xiaoguang
IET SIGNAL PROCESSING, 2023, 17 (06)
[34] THE EMPIRICAL MODE DECOMPOSITION APPLIED TO DYNAMIC POSITIONING SYSTEMS
Morishita, Helio Mitio
Kubota, Leonardo
Vestri, Michaelli Sforsin
Greuell, Solenn
Moratelli, Lazaro, Jr.
OMAE2011: PROCEEDINGS OF THE ASME 30TH INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE AND ARCTIC ENGINEERING, VOL 6: OCEAN ENGINEERING, 2011, : 799 - 806
[35] QRS Complex Detection Based on Ensemble Empirical Mode Decomposition
Henzel, Norbert
INNOVATIONS IN BIOMEDICAL ENGINEERING, 2017, 526 : 286 - 293
[36] Improved Ensemble Empirical Mode Decomposition Method and Its Simulation
Lin, Jinshan
ADVANCES IN INTELLIGENT SYSTEMS, 2012, 138 : 109 - 115
[37] Morphological Filter-Assisted Ensemble Empirical Mode Decomposition
Zhou, Xiaohang
Shan, Deshan
Li, Qiao
MATHEMATICAL PROBLEMS IN ENGINEERING, 2018, 2018
[38] Analysis of ElectroGlottoGraph Signal using Ensemble Empirical Mode Decomposition
Sharma, Rajib
Ramesh, K.
Prasanna, S. R. M.
2014 ANNUAL IEEE INDIA CONFERENCE (INDICON), 2014,
[39] IMPROVEMENT OF ENSEMBLE EMPIRICAL MODE DECOMPOSITION BY OVER-SAMPLING
Bekka, Rais El'hadi
Berrouche, Yaakoub
ADVANCES IN DATA SCIENCE AND ADAPTIVE ANALYSIS, 2013, 5 (03)
[40] THE MULTI-DIMENSIONAL ENSEMBLE EMPIRICAL MODE DECOMPOSITION METHOD
Wu, Zhaohua
Huang, Norden E.
Chen, Xianyao
ADVANCES IN DATA SCIENCE AND ADAPTIVE ANALYSIS, 2009, 1 (03) : 339 - 372

← 1 2 3 4 5 →