Analysis of week‐to‐week variability in skin blood flow measurements using wavelet transforms
Identifieur interne : 008550 ( Main/Exploration ); précédent : 008549; suivant : 008551Analysis of week‐to‐week variability in skin blood flow measurements using wavelet transforms
Auteurs : Yih-Kuen Jan [États-Unis] ; David M. Brienza [États-Unis] ; Mary Jo Geyer [États-Unis]Source :
- Clinical Physiology and Functional Imaging [ 1475-0961 ] ; 2005-09.
Abstract
The study of skin blood flow responses is confounded by temporal variability in blood flow measurements. Spectral analysis has been shown useful in isolating the effects of distinct control mechanisms on various stimuli in the microcirculatory system. However, the sensitivity of spectral analysis to temporal blood blow variability has not been reported. This study was designed to assess week‐to‐week variability in blood flow measurements using wavelet‐based spectrum analysis. Ten healthy, young subjects (mean age ± SD, 30·0 ± 3·1 years) were recruited into the study. Incremental heating (35–45°C, 1° step min−1) was applied on the skin over the sacrum once per week for three consecutive weeks. Wavelet analysis was used to decompose the laser Doppler blood flow signal into frequency bands determined to be associated with endothelial nitric oxide (0·008–0·02 Hz), neurogenic (0·02–0·05 Hz), myogenic (0·05–0·15 Hz), respiratory (0·15–0·4 Hz), and cardiac (0·4–2·0 Hz) control mechanisms. The results showed that coefficients of variation for the power in each frequency band at baseline are smaller than the coefficients of variation of blood flow at baseline or at maximal blood flow ratio (P<0·05). Myogenic and respiratory frequency bands showed the highest coefficients of variation among the five frequency bands. An increase in power in the endothelial nitric oxide frequency band and a decrease in power in the myogenic frequency band of the maximal blood flow response were reproduced in three consecutive weeks. Our study suggests that wavelet analysis is an effective method to overcome temporal variability in skin blood flow measurements.
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DOI: 10.1111/j.1475-097X.2005.00621.x
Affiliations:
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Spectral analysis has been shown useful in isolating the effects of distinct control mechanisms on various stimuli in the microcirculatory system. However, the sensitivity of spectral analysis to temporal blood blow variability has not been reported. This study was designed to assess week‐to‐week variability in blood flow measurements using wavelet‐based spectrum analysis. Ten healthy, young subjects (mean age ± SD, 30·0 ± 3·1 years) were recruited into the study. Incremental heating (35–45°C, 1° step min−1) was applied on the skin over the sacrum once per week for three consecutive weeks. Wavelet analysis was used to decompose the laser Doppler blood flow signal into frequency bands determined to be associated with endothelial nitric oxide (0·008–0·02 Hz), neurogenic (0·02–0·05 Hz), myogenic (0·05–0·15 Hz), respiratory (0·15–0·4 Hz), and cardiac (0·4–2·0 Hz) control mechanisms. The results showed that coefficients of variation for the power in each frequency band at baseline are smaller than the coefficients of variation of blood flow at baseline or at maximal blood flow ratio (P<0·05). Myogenic and respiratory frequency bands showed the highest coefficients of variation among the five frequency bands. An increase in power in the endothelial nitric oxide frequency band and a decrease in power in the myogenic frequency band of the maximal blood flow response were reproduced in three consecutive weeks. Our study suggests that wavelet analysis is an effective method to overcome temporal variability in skin blood flow measurements.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Pennsylvanie</li></region><settlement><li>Pittsburgh</li></settlement><orgName><li>Université de Pittsburgh</li></orgName></list><tree><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Jan, Yih Uen" sort="Jan, Yih Uen" uniqKey="Jan Y" first="Yih-Kuen" last="Jan">Yih-Kuen Jan</name></region><name sortKey="Brienza, David M" sort="Brienza, David M" uniqKey="Brienza D" first="David M." last="Brienza">David M. Brienza</name><name sortKey="Geyer, Mary Jo" sort="Geyer, Mary Jo" uniqKey="Geyer M" first="Mary Jo" last="Geyer">Mary Jo Geyer</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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