Literature DB >> 12214766

Analysis of the photoplethysmographic signal by means of the decomposition in principal components.

Rolando Hong Enríquez1, Miguel Sautié Castellanos, Jersys Falcón Rodríguez, José Luis Hernández Cáceres.   

Abstract

We study the plethysmographic signal using principal component analysis (PCA). By decomposing the signal using this method, we are able to regenerate it again, preserving in the process the functional relationships between the components. We have also found the relative contributions of each specific component to the signal. First return maps have been made for the series of residues of the decomposition. Further analysis using spectral methods has shown that the residues have a 1/f -like structure, which confirms the presence and conservation of this component in the signal and its relative independence with respect to the oscillating component (Hernández et al 2000 Rev. Cubana Inform. Medica 1 5). Our conclusions are that: (i) PCA is a good method to decompose the plethysmographic signal since it preserves the functional relationships in the variables, and this could be potentially useful in finding new clinically relevant indices; (ii) the 1/f process of the plethysmographic signal is preserved in the residues of the decomposed signal when PCA is used; (iii) clinically relevant parameters can potentially be obtained from photoplethysmographic signals when PCA is used.

Mesh:

Year:  2002        PMID: 12214766     DOI: 10.1088/0967-3334/23/3/402

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  5 in total

1.  Motion robust remote photoplethysmography in CIELab color space.

Authors:  Yuting Yang; Chenbin Liu; Hui Yu; Dangdang Shao; Francis Tsow; Nongjian Tao
Journal:  J Biomed Opt       Date:  2016-11-01       Impact factor: 3.170

2.  Motion and Noise Artifact-Resilient Atrial Fibrillation Detection using a Smartphone.

Authors:  Jo Woon Chong; Chae Ho Cho; Fatemehsadat Tabei; Duy Le-Anh; Nada Esa; David D McManus; Ki H Chon
Journal:  IEEE J Emerg Sel Top Circuits Syst       Date:  2018-03-22       Impact factor: 3.916

3.  A Wearable System for Real-Time Continuous Monitoring of Physical Activity.

Authors:  Fabrizio Taffoni; Diego Rivera; Angelica La Camera; Andrea Nicolò; Juan Ramón Velasco; Carlo Massaroni
Journal:  J Healthc Eng       Date:  2018-03-20       Impact factor: 2.682

4.  A novel diversity method for smartphone camera-based heart rhythm signals in the presence of motion and noise artifacts.

Authors:  Fatemehsadat Tabei; Rifat Zaman; Kamrul H Foysal; Rajnish Kumar; Yeesock Kim; Jo Woon Chong
Journal:  PLoS One       Date:  2019-06-19       Impact factor: 3.240

5.  Improving Pulse Rate Measurements during Random Motion Using a Wearable Multichannel Reflectance Photoplethysmograph.

Authors:  Kristen M Warren; Joshua R Harvey; Ki H Chon; Yitzhak Mendelson
Journal:  Sensors (Basel)       Date:  2016-03-07       Impact factor: 3.576

  5 in total

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