earticle

영어

Heart rate variability (HRV) analysis, instantaneous variation in RR intervals time series of electrocardiogram (ECG), is generally used for evaluating autonomic nervous system (ANS) functioning in cardiovascular research and in different human well being related applications. Approximate entropy (ApEn) is a nonlinear metric used to measure the irregularity of a RR interval time series. An increase in ApEn is often associated to increases in complexity. Linear HRV parameters are very sensitive to ECG sampling frequency and low sampling frequency may result in clinically misinterpretation of HRV. In this study consequences of errors in ApEn based HRV induced by ECG sampling frequency have been investigated. Error in ApEn measure of HRV was found to be a function of data length of RR interval time series and ECG sampling frequency. The percentage difference in ApEn was more than 3.5%.for long term data (N=1000), more than 2.5% for medium data (N=500) and less than 1% for short term data (N=200) at low ECG sampling frequency of 125 Hz with respect to reference values at 2000 Hz. Thus, the results of indices such as ApEn when applied to time series with low ECG sampling should be regarded with caution.