Demographic Characterization of Heart Rate Variability (HRV)

Introduction

The rate and modulation of the heart beat i.e. heart rate variability (HRV) are controlled by the autonomic nervous system. Sympathetic activation decreases and parasympathetic action of the heart increases HRV. Measurement of heart rate variability (HRV) provides a non-invasive method to obtain reliable and reproducible information on the autonomic modulation of heart rate and has become an important tool for risk assessment. Other than relating to various physiological and clinical correlations, HRV has been found to correlate with, e.g., age, mental and physical stress, and attention, sees, geographical locations, altitude, racial differences, etc. The Chapter is focused on demographic characterization of the Heart Rate Variability parameters. A short term (5 minutes) recording is performed on the subjects selected randomly in the plains (reference data) and hills (research data). HRV analysis is performed in three domains and statistically analyzed for characterization.

The objective being, to characterize the population of the north eastern hilly regions of West Bengal and to have a comparison with the population residing in the plains of the region using different analysis methods. Thus both male and female subjects from different parts of hills and plains of the region were selected for the present study. Five hundred (500) subjects were selected on stratified random selection basis from 2007 to 2010. The population is divided into two groups, viz.

• 1.

  The hill population (400 healthy subjects): The sample of four hundred subjects representing the hill population has 262 males and 138 females aged from 17 to 76 with a mean age of 34± 13.07 and 17 to 86 years with a mean age of 34.1 ± 11.4 respectively.

• 2.

  The plains population (100 healthy subjects): The sample of one hundred subjects representing the plains population has 66 males and 34 females aged from 17 to 56 with a mean age of 27.68± 9.394 and 18 to 81 years with a mean age of 28.1 ± 12.2006 respectively.

The data collection was done in two steps, viz. Schedule by asking questions and noting down the same in one part and physiological data (Heart Rate parameters) collected from the subjects under various conditions by using Suunto T6 Heart Rate Monitor. Analysis of the parameters was carried out using KUBIOS HRV 2.0 software. Entire statistical analyses were performed using SPSS 13.0. An ANN has been designed using MATLAB R2009b neural network toolbox to characterize a person whether he belongs to hill or plains. The network has been trained on a test population and has been validated with another set of data in both categories of population.

Background

An extent of experimental works emphasize that various cardiovascular variables like heart rate and blood pressure fluctuate from beat-to-beat. Ancient Physicians noted the temporal fluctuations in cardiovascular signals but overlooked the possible significance of the beat-to-beat fluctuation. The variability was treated as noise and it was either ignored or averaged out. Stephen Hales (1733) became the pioneer to report beat-to-beat heart rate variability to be synchronous with respiration and obstetrics became the maiden field in which the potential clinical significance of beat-to-beat variability in cardiovascular signals was recognized. The importance of sinus arrhythmia was described in relation to fetal monitoring in 1965 (Heart rate variability, 1996; Bernston et al., 1997). The variability correlated with fetal viability as step down of beat-to-beat variability indicated fetal compromise (Heart rate variability, 1996). Earlier studies indicate HRV measurements to be based on simple measurements of RR intervals in diabetic studies.

An in depth research have shown that decreased fluctuation of RR interval is not noise, but implicates an increased risk for arrhythmic events and an increased mortality rate in patients with a previous myocardial infarction. Time - frequency domain measures and nonlinear studies of heart rate variability have provided portent information and increased possibilities to perform noninvasive studies on the significance of changes in the regulation of heart rate behavior.