NDLI: Estimation of blood pressure variability using independent component analysis of photoplethysmographic signal

Content Provider	IEEE Xplore Digital Library
Author	Abe, M. Yoshizawa, M. Sugita, N. Tanaka, A. Chiba, S. Yambe, T. Nitta, S.-i.
Copyright Year	2009
Description	Author affiliation: Sharp Corporation, 1-9-2 Nakase, Mihama-ku, Chiba 261-8520, Japan (Chiba, S.) \|\| Institute of Development, Aging and Cancer, Tohoku University, 4-1 Seiryo-cho, Aoba-ku, Sendai 980-8575, Japan (Yambe, T.; Nitta, S.-i.) \|\| Graduate School of Engineering, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan (Sugita, N.) \|\| Research Division on Advanced Information Technology, Cyberscience Center, Tohoku University, 6-6-05 Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan (corresponding author to provide (Abe, M.; Yoshizawa, M.) \|\| Faculty of Symbiotic Systems Science, Fukushima University, 1 Kanayagawa, Fukushima 960-1296, Japan (Tanaka, A.)
Abstract	The maximum cross-correlation coefficient ρmax 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 ρmax. The present study has proposed an easier method for obtaining ρmax 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 ρmax 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 ρmax by using the ICA to extract blood pressure information from the PPG signal.
Starting Page	348
Ending Page	351
File Size	323433
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5333155
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Blood pressure variability Independent component analysis Pressure measurement Blood pressure Heart rate variability Frequency Baroreflex Fingers Feature extraction Data mining
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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