PCA-Based Multi-Wavelength Photoplethysmography Algorithm for Cuffless Blood Pressure Measurement on Elderly Subjects

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • Jing Liu
  • Shirong Qiu
  • Ningqi Luo
  • Sze-Kei Lau
  • Hui Yu
  • Timothy Kwok
  • Ni Zhao

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number9122530
Pages (from-to)663-673
Journal / PublicationIEEE Journal of Biomedical and Health Informatics
Volume25
Issue number3
Online published22 Jun 2020
Publication statusPublished - Mar 2021

Abstract

The prevalence of hypertension has made blood pressure (BP) measurement one of the most wanted functions in wearable devices for convenient and frequent self-assessment of health conditions. The widely adopted principle for cuffless BP monitoring is based on arterial pulse transit time (PTT), which is measured with electrocardiography and photoplethysmography (PPG). To achieve cuffless BP monitoring with more compact wearable electronics, we have previously conceived a multi-wavelength PPG (MWPPG) strategy to perform BP estimation from arteriolar PTT, requiring only a single sensing node. However, challenges remain in decoding the compounded MWPPG signals consisting of both heterogeneous physiological information and motion artifact (MA). In this work, we proposed an improved MWPPG algorithm based on principal component analysis (PCA) which matches the statistical decomposition results with the arterial pulse and capillary pulse. The arteriolar PTT is calculated accordingly as the phase shift based on the entire waveforms, instead of local peak lag time, to enhance the feature robustness. Meanwhile, the PCA-derived MA component is employed to identify and exclude the MA-contaminated segments. To evaluate the new algorithm, we performed a comparative experiment (N = 22) with a cuffless MWPPG measurement device and used double-tube auscultatory BP measurement as a reference. The results demonstrate the accuracy improvement enabled by the PCA-based operations on MWPPG signals, yielding errors of 1.44 ± 6.89 mmHg for systolic blood pressure and -1.00 ± 6.71 mm Hg for diastolic blood pressure. In conclusion, the proposed PCA-based method can improve the performance of MWPPG in wearable medical devices for cuffless BP measurement.

Research Area(s)

  • cuffless blood pressure measurement, multi-wavelength photoplethysmography, Principal component analysis

Citation Format(s)

PCA-Based Multi-Wavelength Photoplethysmography Algorithm for Cuffless Blood Pressure Measurement on Elderly Subjects. / Liu, Jing; Qiu, Shirong; Luo, Ningqi; Lau, Sze-Kei; Yu, Hui; Kwok, Timothy; Zhang, Yuan-Ting; Zhao, Ni.

In: IEEE Journal of Biomedical and Health Informatics, Vol. 25, No. 3, 9122530, 03.2021, p. 663-673.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review