Multi-scale complexity analysis of cardiac variability time series in adult and mid-aged females

Multi-scale entropy (MSE) analysis is being used as a complexity measure to quantify the hidden complexity of heart rate variability (HRV) signals in healthy and diseased states since quite some time. Thereafter the refined MSE (RMSE) was introduced in which refinement was made in the elimination of fast temporal scales by replacing the low pass filter used in original MSE with a butter worth low pass filter. The threshold value `r´ is updated as a function of standard deviation (SD) of the filtered scaled time series. In the present study comparative analysis of both these techniques have been done on cardiac time series derived from adult female and mid-aged female groups for a data length of N=4000 and template matching length of m=2. Both these techniques assign higher entropy value to the adult female group than that of mid aged female group. It has been observed that HRV of adult female acquire more complex pattern than that of mid aged female group and it reduces with ageing. RMSE analysis results in better discrimination between both these groups (p<;0.01).