IJAIEM

S.Gouthami, N.Ankitha

Abstract

A change in autonomic nervous system (ANS) activity is one hypothesis that tries to explain why obese persons have an increased risk of cardiovascular disease (CVD). Monitoring heart rate variability (HRV) allows one to detect shifts in ANS activity. It is possible to quantify ANS activity non-invasively using linear and non-linear HRV features. To better understand the effects of obesity on the autonomic nervous system, this study sought to measure HRV. Synthetic minority oversampling (SMOTE) was used to increase the number of control and obese persons from sixteen to forty-eight. The initial sample for the research consisted of sixteen women and sixteen men, with ages ranging from twenty-five to fifty. When we used the Independent t test to compare the two datasets, we discovered a statistically significant difference. According to the study, a decrease in parasympathetic activity leads to an imbalance in sympathovagal tone. Using the machine learning approach allowed us to c