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This Article Full Text Full Text (PDF) All Versions of this Article: 294/1/H362    most recent 01061.2007v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Web of Science (3) Citing Articles via Google Scholar Google Scholar Articles by Chen, X. Articles by Mukkamala, R. Search for Related Content PubMed PubMed Citation Articles by Chen, X. Articles by Mukkamala, R.

Selective quantification of the cardiac sympathetic and parasympathetic nervous systems by multisignal analysis of cardiorespiratory variability

Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan

Submitted 12 September 2007 ; accepted in final form 5 November 2007

Heart rate (HR) power spectral indexes are limited as measures of the cardiac autonomic nervous systems (CANS) in that they neither offer an effective marker of the β-sympathetic nervous system (SNS) due to its overlap with the parasympathetic nervous system (PNS) in the low-frequency (LF) band nor afford specific measures of the CANS due to input contributions to HR [e.g., arterial blood pressure (ABP) and instantaneous lung volume (ILV)]. We derived new PNS and SNS indexes by multisignal analysis of cardiorespiratory variability. The basic idea was to identify the autonomically mediated transfer functions relating fluctuations in ILV to HR (ILVHR) and fluctuations in ABP to HR (ABPHR) so as to eliminate the input contributions to HR and then separate each estimated transfer function in the time domain into PNS and SNS indexes using physiological knowledge. We evaluated these indexes with respect to selective pharmacological autonomic nervous blockade in 14 humans. Our results showed that the PNS index derived from the ABPHR transfer function was correctly decreased after vagal and double (vagal + β-sympathetic) blockade (P < 0.01) and did not change after β-sympathetic blockade, whereas the SNS index derived from the same transfer function was correctly reduced after β-sympathetic blockade in the standing posture and double blockade (P < 0.05) and remained the same after vagal blockade. However, this SNS index did not significantly decrease after β-sympathetic blockade in the supine posture. Overall, these predictions were better than those provided by the traditional high-frequency (HF) power, LF-to-HF ratio, and normalized LF power of HR variability.

heart rate variability; modeling; power spectral analysis; system identification; transfer function