This article presents a comprehensive system for automatic heart rate (HR) detection. The system is robust and resistant to disturbances (noise, interferences, artifacts) occurring mainly during epileptic seizures. ECG signal filtration (IIR) and normalization due to skewness and standard deviation were used as preprocessing steps. A key element of the system is a reference QRS complex pattern calculated individually for each ECG recording. Next, a cross-correlation of the reference QRS pattern with short, normalized ECG windows is calculated and the maxima of the correlation are found (R-wave locations). Determination of the RR intervals makes possible calculation of heart rate changes and also heart rate variability (HRV). The algorithm was tested using a simulation in which a noise of an amplitude several times higher than ECG standard deviation levels was added. The proposed algorithm is characterized by high QRS detection accuracy, and high sensitivity and specificity. The algorithm proved to be useful in clinical practice, where it was used to automatically determine HR for ECG signals recorded before and during 58 focal seizures in 56 adult patients with intractable temporal lobe epilepsy.
Keywords: Epilepsy; HR; Heart rate; Heart rate variability; QRS detection; R-wave; RR interval.