Estimation of blood pressure variability using independent component analysis of photoplethysmographic signal.

Makoto Abe, Makoto Yoshizawa, Norihiro Sugita, Akira Tanaka, Shigeru Chiba, Tomoyuki Yambe, Shin ichi Nitta

Research output: Contribution to journalArticlepeer-review

Abstract

The maximum cross-correlation coefficient rho(max) between blood pressure variability and heart rate variability, whose frequency components are limited to the Mayer wave-related band, is a useful index to evaluate the state of the autonomic nervous function related to baroreflex. However, measurement of continuous blood pressure with an expensive and bulky measuring device is required to calculate rho(max). The present study has proposed an easier method for obtaining rho(max) with measurement of finger photoplethysmography (PPG). In the proposed method, independent components are extracted from feature variables specified by the PPG signal by using the independent component analysis (ICA), and then the most appropriate component is chosen out of them so that the rho(max) based on the component can fit its true value. The results from the experiment with a postural change performed in 17 healthy subjects suggested that the proposed method is available for estimating rho(max) by using the ICA to extract blood pressure information from the PPG signal.

Original languageEnglish
Pages (from-to)348-351
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Publication statusPublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Fingerprint Dive into the research topics of 'Estimation of blood pressure variability using independent component analysis of photoplethysmographic signal.'. Together they form a unique fingerprint.

Cite this