A Study of the Model Order Variation with Activities in Autonomic Bands and Comparison of Ar Methods of Pse of Heart Rate Time Series

A Study of the Model Order Variation with Activities in Autonomic Bands and Comparison of Ar Methods of Pse of Heart Rate Time Series

  • Submitted By: avneet
  • Date Submitted: 07/08/2009 9:27 PM
  • Category: Miscellaneous
  • Words: 3409
  • Page: 14
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Abstract— The aim of this study was to analyze the variation in model orders with autonomic activities in young and old subjects. We studied five young (21-34 years old) band five elderly (68-85 years old) rigorously screened healthy subjects undergone 120 minutes of continuous spine resting from the fantasia database. Spectral analysis of HRV was performed on 2 hours ectopic free recordings. PSE was done for model orders 6,10,16,20,22 using burg, covariance and Yule walker methods and values of power in autonomic bands was also estimated. This paper results convey that resolvable and smoother power peaks are obtained at model order p=10 for younger subjects and for older subjects smooth and clear power peaks are obtained at model order of p=6 for older subjects These results exhibits that covariance method shows best peaks in young and old subjects. Thus peaks for higher model orders shows that lower amplitude predicts that HRV diminishes with age and in normal ageing in absence of disease is associated with lesser parasympathetic regulation of heart rate .

Keywords—HRV, PSE,

INTRODUCTION
HRV is a measure of the beat to beat variations in heart rate and blood pressure provides an important tool for understanding cardiovascular regulation [1]. It is usually calculated by analyzing a time series of beat-to-beat intervals from the ECG. One application of particular interest is the assessment of the effects of aging on an analysis of changes in RR intervals. A large number of studies have provided evidence that HRV measurements evaluate the autonomic nervous system.
After its measurement there are various methods for its analysis. These methods are like time domain methods in which RR interval time series covers the calculation of several common statistical indices, frequency domain methods which provides estimation of the variability distributed as a function of frequency and the power spectral density can be calculated by FFT and by...

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