An Analysis of HRV Spectrum for Observing ANS Variations Caused by Sympathectomy and Vagotomy.
10.11637/kjpa.1999.12.2.289
- Author:
Hyung Sok YEO
1
;
Jae Joong IM
;
Hwan Tae PARK
Author Information
1. Samsung Biomedical Research Institute, Korea.
- Publication Type:Original Article
- Keywords:
Autonomic nervous system;
HRV spectrum;
Sympathectomy;
Vagotomy;
ECG
- MeSH:
Animals;
Autonomic Nervous System;
Cardiovascular Diseases;
Cardiovascular System;
Classification;
Electrocardiography;
Humans;
Mortality;
Parasympathetic Nervous System;
Rats;
Spectrum Analysis;
Sympathectomy*;
Vagotomy*
- From:Korean Journal of Physical Anthropology
1999;12(2):289-296
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
Increased death rate resulted from cardiovascular disease called for the study on the autonomic nervous system and cardiovascular system. It is known that an HRV (heart rate variability) spectrum analysis based on ECG (electrocardiograph) signals could be used to define activity of sympathetic and parasympathetic nervous system noninvasively. However, it is important to prove whether suggested HRV analysis method could provide the useful information for observing autonomic nervous system quantitatively and objectively before clinical application. In this study, 14 rats were used and divided into two groups, sympathectomy group and vagotomy group, respectively. During the experiment, ECGs of rats were collected three times at each experimental condition. After the application of Berger's series algorithm to the ECG raw data, HRV spectrum was obtained via FFT (fast Fourier transform). Power contents for each frequency bands were calculated from HRV waveforms. Two peak values, HF (high frequency) and LF(low frequency), representing autonomic nervous system status were used to extract the parameter, HF/LF ratio. Results showed that HF/LF values were increased for the sympathectomy group and decreased for the vagotomy group. It implies that the variations in HF/LF components exhibits the information for the classification of ANS(autonomic nervous system) function quantitatively. HRV analysis algorithm developed from this study could be expanded for the observation of autonomic nervous system variations in human.
