DocumentCode :
868816
Title :
Nonlinear analysis of the separate contributions of autonomic nervous systems to heart rate variability using principal dynamic modes
Author :
Zhong, Yuru ; Wang, Hengliang ; Ju, Ki Hwan ; Jan, Kung-Ming ; Chon, Ki H.
Author_Institution :
Dept. of Biomed. Eng., State Univ. of New York, Stony Brook, NY, USA
Volume :
51
Issue :
2
fYear :
2004
Firstpage :
255
Lastpage :
262
Abstract :
This paper introduces a modified principal dynamic modes (PDM) method, which is able to separate the dynamics of sympathetic and parasympathetic nervous activities. The PDM is based on the principle that among all possible choices of expansion bases, there are some that require the minimum number of basis functions to achieve a given mean-square approximation of the system output. Such a minimum set of basis functions is termed PDMs of the nonlinear system. We found that the first two dominant PDMs have similar frequency characteristics for parasympathetic and sympathetic activities, as reported in the literature. These results are consistent for all nine of our healthy human subjects using our modified PDM approach. Validation of the purported separation of parasympathetic and sympathetic activities was performed by the application of the autonomic nervous system blocking drugs atropine and propranolol. With separate applications of the respective drugs, we found a significant decrease in the amplitude of the waveforms that correspond to each nervous activity. Furthermore, we observed near complete elimination of these dynamics when both drugs were given to the subjects. Comparison of our method to the conventional low-frequency/high-frequency ratio shows that our proposed approach provides more accurate assessment of the autonomic nervous balance. Our nonlinear PDM approach allows a clear separation of the two autonomic nervous activities, the lack of which has been the main reason why heart rate variability analysis has not had wide clinical acceptance.
Keywords :
electrocardiography; mean square error methods; medical signal processing; neurophysiology; nonlinear dynamical systems; spectral analysis; QRS complexes; atropine; autonomic nervous systems; blocking drugs; expansion bases; heart rate variability; mean-square approximation; nonlinear analysis; nonlinear physiological systems; parasympathetic nervous activities; power spectrum; principal dynamic modes; propranolol; separate contributions; surface electrocardiogram; sympathetic nervous activities; Autonomic nervous system; Biomedical engineering; Drugs; Hafnium; Heart rate variability; Humans; Myocardium; Nonlinear dynamical systems; Nonlinear systems; Spectral analysis; Adult; Atropine; Autonomic Nervous System; Computer Simulation; Electrocardiography; Heart; Heart Conduction System; Heart Rate; Humans; Male; Models, Cardiovascular; Models, Neurological; Nonlinear Dynamics; Parasympathetic Nervous System; Principal Component Analysis; Propranolol; Sympathetic Nervous System;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2003.820401
Filename :
1262103
Link To Document :
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