Effects of Smoking on Heart Rate Variability through Information Based Similarity Index

Smoking is a major public health problem. In this paper, we introduce a new approach regarding the analysis of the Heart Rate Variability (HRV) signals using Information based Similarity Index Method. From Electrocardiogram (ECG) signals first HRV signals extracted using Moving Window iteration technique. Finally study the changes of the R-R interval signals before and after smoking of twenty young male volunteers using 3 bit rank from Symbolic Dynamics which is extracted from Forced Dynamics of the original signals. Then we compare probability distributions between each pair of subjects both in normal and smoking states by using Q-Q plot. Our experimental provides satisfactory results in this context.