Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

The Diabetes Educator

Click here for more information on The Virtual Advisor

Sign In to gain access to subscriptions and/or personal tools.
Biological Research For Nursing
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Schumacher, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Schumacher, A.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Linear and Nonlinear Approaches to the Analysis of R-R Interval Variability

Autumn Schumacher, PhD, RN

Nell Hodgson Woodruff School of Nursing at Emory University, Atlanta, Georgiaaschuma{at}emory.edu

Analysis techniques derived from linear and non-linear dynamics systems theory qualify and quantify physiological signal variability. Both clinicians and researchers use physiological signals in their scopes of practice. The clinician monitors patients with signal-analysis technology, and the researcher analyzes physiological data with signal-analysis techniques. Understanding the theoretical basis for analyzing physiological signals within one’s scope of practice ensures proper interpretation of the relationship between physiological function and signal variability. This article explains the concepts of linear and nonlinear signal analysis and illustrates these concepts with descriptions of power spectrum analysis and recurrence quantification analysis. This article also briefly describes the relevance of these 2 techniques to R-to-R wave interval (i.e., heart rate variability) signal analysis and demonstrates their application to R-to-R wave interval data obtained from an isolated rat heart model.

Key Words: linearity • nonlinearity • power spectrum analysis • recurrence quantification analysis • heart rate variability • isiolated rat heart model

Biological Research For Nursing, Vol. 5, No. 3, 211-221 (2004)
DOI: 10.1177/1099800403260619


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
Phil Trans R Soc AHome page
A. Voss, S. Schulz, R. Schroeder, M. Baumert, and P. Caminal
Methods derived from nonlinear dynamics for analysing heart rate variability
Phil Trans R Soc A, January 28, 2009; 367(1887): 277 - 296.
[Abstract] [Full Text] [PDF]


Home page
Biol Res NursHome page
A. M. Schumacher, J. P. Zbilut, C. L. Webber Jr., D. W. Schwertz, and M. R. Piano
Detection of cardiac variability in the isolated rat heart.
Biol Res Nurs, July 1, 2006; 8(1): 55 - 66.
[Abstract] [PDF]


Home page
Biol Res NursHome page
R. L. Burr, S. A. Motzer, W. Chen, M. J. Cowan, R. J. Shulman, and M. M. Heitkemper
Heart Rate Variability and 24-hour Minimum Heart Rate.
Biol Res Nurs, April 1, 2006; 7(4): 256 - 267.
[Abstract] [PDF]


Home page
Biol Res NursHome page
M. S. Faulkner, L. Quinn, J. H. Rimmer, and B. H. Rich
Cardiovascular Endurance and Heart Rate Variability in Adolescents With Type 1 or Type 2 Diabetes
Biol Res Nurs, July 1, 2005; 7(1): 16 - 29.
[Abstract] [PDF]