In the electrocardiograph (ECG), R-wave is the positive upward deflection in the QRS complex which represents the depolarization of both left and right ventricles. Accurate detection of the R-wave peaks in the ECG plays a primary role in the construction and analysis of the heart rate variability (HRV). Numerous methods have been proposed to enhance the robustness and accuracy of the automatic detection. The majority of these methods have been developed for adult ECG and may not perform adequately in the case of the newborn. In this study, we analysed the performance of four R-wave detection methods that were applied on newborn piglet ECG data. These methods are based on: first derivative, wavelet transform, and nonlinear transform. The results of our performance analysis showed that the nonlinear approach based on the Hilbert transform marginally outperformed the others, with the highest sensitivity (Se) of 99 .95%, the lowest detection error(ER) of 0.12% and a high positive prediction (+P) of 99.93%.