Accurate R peak detection and advanced preprocessing of normal ECG for heart rate variability analysis

Heart rate variability (HRV) analysis is well-known to give information about the autonomic heart rate modulation mechanism. In order to avoid erroneous conclusions, it is of great importance that only sinus rhythms are present in the tachogram. Therefore, preprocessing of the RR interval time series is necessary. This paper presents an advanced automated algorithm to preprocess RR intervals obtained from a normal ECG. Validation of this algorithm was performed on one hour ECG signals of 20 pregnant women. R peaks before and after preprocessing were manually revised for spurious and missed R peak detections. Before preprocessing, more than 1% of the detected R peaks were incorrect while preprocessing corrected more than 94% of these errors leading to an overall error rate of 0.06%. Our automated preprocessing technique therefore restricts the manual data check to the absolute minimum and allows a reliable HRV analysis.