Ensemble Empirical Mode Decomposition With Principal Component Analysis: A Novel Approach for Extracting Respiratory Rate and Heart Rate From Photoplethysmographic Signal | IEEE Journals & Magazine | IEEE Xplore

Ensemble Empirical Mode Decomposition With Principal Component Analysis: A Novel Approach for Extracting Respiratory Rate and Heart Rate From Photoplethysmographic Signal


Abstract:

The photoplethysmographic (PPG) signal measures the local variations of blood volume in tissues, reflecting the peripheral pulse modulated by cardiac activity, respiratio...Show More

Abstract:

The photoplethysmographic (PPG) signal measures the local variations of blood volume in tissues, reflecting the peripheral pulse modulated by cardiac activity, respiration, and other physiological effects. Therefore, PPG can be used to extract the vital cardiorespiratory signals like heart rate (HR), and respiratory rate (RR) and this will reduce the number of sensors connected to the patient's body for recording these vital signs. In this paper, we propose an algorithm based on ensemble empirical mode decomposition with principal component analysis (EEMD-PCA) as a novel approach to estimate HR and RR simultaneously from PPG signal. To examine the performance of the proposed algorithm, we used 310 (from 35 subjects) and 632 (from 42 subjects) epochs of simultaneously recorded electrocardiogram, PPG, and respiratory signal extracted from MIMIC (Physionet ATM data bank) and Capnobase database, respectively. Results of EEMD-PCA-based extraction of HR and RR from PPG signal showed that the median RMS error (1st and 3rd quartiles) obtained in MIMIC data set for RR was 0.89 (0, 1.78) breaths/min, for HR was 0.57 (0.30, 0.71) beats/min and in Capnobase data set it was 2.77 (0.50, 5.9) breaths/min and 0.69 (0.54, 1.10) beats/min for RR and HR, respectively. These results illustrated that the proposed EEMD-PCA approach is more accurate in estimating HR and RR than other existing methods. Efficient and reliable extraction of HR and RR from the pulse oximeter's PPG signal will help patients for monitoring HR and RR with low cost and less discomfort.
Published in: IEEE Journal of Biomedical and Health Informatics ( Volume: 22, Issue: 3, May 2018)
Page(s): 766 - 774
Date of Publication: 07 March 2017

ISSN Information:

PubMed ID: 28287994

References

References is not available for this document.