Ecg artifacts and poincaré plot based heart rate variability

Abstract

Abstract: The analysis of beat to beat fluctuations of heart rate known as heart rate variability (HRV) become a non-invasive clinical research tool to study the modulation that the autonomic nervous system exerts on the cardiovascular system. The missing RR intervals contribute a serious limitation to HRV analysis. The linear HRV measures are very sensitive to ECG artifacts. The objective of present study was to evaluate the robustness of Poincaré plot analysis in presence of missing RR intervals. Poincaré plot is a visual tool in which each RR interval is plotted as a function of previous RR interval. The Poincaré plot provides summary as well as detailed beat-to-beat information on the behavior of the heart. The study involves RR interval time-series data of 25 healthy volunteers. The ectopic free RR interval tachograms with length N=1000 were derived from Lead-II ECG recordings having a sampling frequency of 500 Hz. In each data set, consecutive RR interval data were randomly selected for removal, and the data length removed was increased from 0 to 100 RR intervals in an increment of 5 RR intervals. Two random selections of RR intervals were made to analyze the average effects of the missing data. In each case, the Poincaré plot (SD1 and SD2) based HRV parameters were calculated. Mean relative errors were found to be less than 1.8 for SD1 and SD2 even in the presence of 100 missing RR intervals. Poincaré plot parameters are found to be more robust than linear measures to missing RR intervals