Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2010-7-27
pubmed:abstractText
Human heartbeat intervals are known to have nonlinear and nonstationary dynamics. In this paper, we propose a model of R-R interval dynamics based on a nonlinear Volterra-Wiener expansion within a point process framework. Inclusion of second-order nonlinearities into the heartbeat model allows us to estimate instantaneous heart rate (HR) and heart rate variability (HRV) indexes, as well as the dynamic bispectrum characterizing higher order statistics of the nonstationary non-gaussian time series. The proposed point process probability heartbeat interval model was tested with synthetic simulations and two experimental heartbeat interval datasets. Results show that our model is useful in characterizing and tracking the inherent nonlinearity of heartbeat dynamics. As a feature, the fine temporal resolution allows us to compute instantaneous nonlinearity indexes, thus sidestepping the uneven spacing problem. In comparison to other nonlinear modeling approaches, the point process probability model is useful in revealing nonlinear heartbeat dynamics at a fine timescale and with only short duration recordings.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-10365957, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-10442397, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-11258383, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-11538314, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-11607165, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-11686624, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-11755014, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-11875196, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-11962771, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-12185014, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-12190613, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-14765698, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-16009791, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-16973939, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-1741525, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-17415661, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-17851254, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-19183809, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-19566278, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-19669436, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-7729840, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-8116911, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-8598068, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-8637921, http://linkedlifedata.com/resource/pubmed/commentcorrection/20172783-9333237
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1558-2531
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
57
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1335-47
pubmed:dateRevised
2011-7-28
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Characterizing nonlinear heartbeat dynamics within a point process framework.
pubmed:affiliation
Neuroscience Statistics Research Laboratory, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA. zhechen@neurostat.mit.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural