Literature DB >> 8795444

Poincaré plot of heart rate variability allows quantitative display of parasympathetic nervous activity in humans.

P W Kamen1, H Krum, A M Tonkin.   

Abstract

1. Time domain summary statistics and frequency domain parameters can be used to measure heart rate variability. More recently, qualitative methods including the Poincaré plot have been used to evaluate heart rate variability. The aim of this study was to validate a novel method of quantitative analysis of the Poincaré plot using conventional statistical techniques. 2. Beat-to-beat heart rate variability was measured over a relatively short period of time (10-20 min) in 12 healthy subjects aged between 20 and 40 years (mean 30 +/- 7 years) during (i) supine rest, (ii) head-up tilt (sympathetic activation, parasympathetic nervous system activity withdrawal), (iii) intravenous infusion of atropine (parasympathetic nervous system activity withdrawal), and (iv) after overnight administration of low-dose transdermal scopolamine (parasympathetic nervous system augmentation). 3. The "width' of the Poincaré plot, as quantified by SD delta R-R (the difference between successive R-R intervals), was determined at rest (median 48.9, quartile range 20 ms) and found to be significantly reduced during tilt (median 19.1, quartile range 13.7 ms, P < 0.01) and atropine administration (median 7.1, quartile range 5.7 ms, P < 0.01) and increased by scopolamine (median 79.3, quartile range 33 ms, P < 0.01). Furthermore, log variance of delta R-R intervals correlated almost perfectly with log high-frequency (0.15-0.4 Hz) power (r = 0.99, P < 0.01). 4. These findings strongly suggest that the "width' of the Poincaré plot is a measure of parasympathetic nervous system activity. The Poincaré plot is therefore a quantitative visual tool which can be applied to the analysis of R-R interval data gathered over relatively short time periods.

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Year:  1996        PMID: 8795444     DOI: 10.1042/cs0910201

Source DB:  PubMed          Journal:  Clin Sci (Lond)        ISSN: 0143-5221            Impact factor:   6.124


  78 in total

1.  Quantitative Poincaré plot analysis of heart rate variability: effect of endurance training.

Authors:  Laurent Mourot; Malika Bouhaddi; Stéphane Perrey; Jean-Denis Rouillon; Jacques Regnard
Journal:  Eur J Appl Physiol       Date:  2003-09-04       Impact factor: 3.078

2.  Heart rate variability during cycloergometric exercise or judo wrestling eliciting the same heart rate level.

Authors:  François Cottin; François Durbin; Yves Papelier
Journal:  Eur J Appl Physiol       Date:  2003-10-14       Impact factor: 3.078

Review 3.  Heart rate variability: a review.

Authors:  U Rajendra Acharya; K Paul Joseph; N Kannathal; Choo Min Lim; Jasjit S Suri
Journal:  Med Biol Eng Comput       Date:  2006-11-17       Impact factor: 2.602

4.  Graphical and numerical evaluation of continuous glucose sensing time lag.

Authors:  Boris P Kovatchev; Devin Shields; Marc Breton
Journal:  Diabetes Technol Ther       Date:  2009-03       Impact factor: 6.118

5.  A method for analyzing temporal patterns of variability of a time series from Poincare plots.

Authors:  Mikkel Fishman; Frank J Jacono; Soojin Park; Reza Jamasebi; Anurak Thungtong; Kenneth A Loparo; Thomas E Dick
Journal:  J Appl Physiol (1985)       Date:  2012-05-03

6.  Poincaré plot analysis of autocorrelation function of RR intervals in patients with acute myocardial infarction.

Authors:  Shin-Shin Chuang; Kung-Tai Wu; Chen-Yang Lin; Steven Lee; Gau-Yang Chen; Cheng-Deng Kuo
Journal:  J Clin Monit Comput       Date:  2013-12-20       Impact factor: 2.502

7.  P-wave dispersion in endogenous and exogenous subclinical hyperthyroidism.

Authors:  R Gen; E Akbay; A Camsari; T Ozcan
Journal:  J Endocrinol Invest       Date:  2009-07-28       Impact factor: 4.256

8.  Type 5 adenylyl cyclase plays a major role in stabilizing heart rate in response to microgravity induced by parabolic flight.

Authors:  Satoshi Okumura; Takashi Tsunematsu; Yunzhe Bai; Qibin Jiao; Shinji Ono; Sayaka Suzuki; Reiko Kurotani; Motohiko Sato; Susumu Minamisawa; Satoshi Umemura; Yoshihiro Ishikawa
Journal:  J Appl Physiol (1985)       Date:  2008-05-01

9.  Heart rate variability effects of an agonist or antagonists of the beta-adrenoceptor assessed with scatterplot and sequence analysis.

Authors:  B Silke; J G Riddell
Journal:  Clin Auton Res       Date:  1998-06       Impact factor: 4.435

10.  Identifying diabetic patients with cardiac autonomic neuropathy by heart rate complexity analysis.

Authors:  Ahsan H Khandoker; Herbert F Jelinek; Marimuthu Palaniswami
Journal:  Biomed Eng Online       Date:  2009-01-29       Impact factor: 2.819

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