Correlation Analysis of Heart Rate Variability and Respiratory Frequency Under Sinus Arrhythmia Condition
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Abstract
The heart is not just a muscular organ that serves to pump and make blood flow in the
whole body, the heart, being connected to the brain and the autonomic nervous
system, is emotional in its feelings and expression. The heart rate variability (HRV)
test is designed to give an indication of the state of the biological systems that
regulate cardiac activity. The cardiac system functions best when it is regulated by the
autonomic circuit. When homeostasis is broken i.e. the natural balance is disturbed,
higher levels of the central regulatory system dominate cardiac activity.
These changes in regulation are reflected in the variability of the heart rhythm. Beatto-
beat changes in cardiac signals or heart rate variability is controlled by the two
branches of autonomic nervous system (ANS) in a very complex manner. It is clear
that HRV analysis with and without respiratory information provides different results.
The differences become more obvious when respiration rate is low. Furthermore,
many standard ANS tests include deep breathing test, which is to stimulate
parasympathetic branch of ANS. Therefore for accurate assessment of the ANS
activity, one must include the effect of respiration in HRV analysis. This kind of a
change is only observed when respiratory peak is used in HRV analysis to locate high
frequency area then estimating the power. Employing respiratory signal in HRV
analysis provides more accurate isolation of sympathetic and parasympathetic
activity, which provides a better diagnostic tool in assessing human ANS.
Power spectral analysis of HRV measure changes in total ANS power and
sympathetic and parasympathetic balance that occur during different emotional states.
There are many situations where heart rate changes rapidly over time, and the control
of those changes is of considerable interest.
Our thesis work focuses on analyzing the correlation between heart rate variability
and respiratory frequency using MATLAB software tool. Pearson correlation
coefficient is used for this purpose. Thereafter, various parameters like noise, high
frequency component are varied to find the effect of respiration on heart rate
variability. Hence, a better understanding is attained about autonomic control of
rapidly changing signals. As a result of this methodology, pathophysiological
conditions of paramount importance, such as arterial hypertension, myocardial
ischemia, sudden cardiac death, and heart failure might soon undergo a novel scrutiny with practical implications. It is generally accepted that RSA amplitude is a
noninvasive marker of the activity of the parasympathetic nervous system, and it can
therefore be used to infer relative changes in parasympathetic cardiac tone.
Description
ELECTRICAL AND INSTRUMENTATION ENGINEERING
DEPARTMENT, THAPAR UNIVERSITY
PATIALA – 147004
