Time-frequency analysis of heart rate variability (HRV) provides relevant clinical information. However, time-frequency analysis is very sensitive to artefacts. Artefacts that are present in heart rate recordings may be corrected, but this reduces the variability in the signal and therefore adversely affects the accuracy of calculated spectral estimates. To overcome this limitation of traditional techniques for time-frequency analysis, a new continuous wavelet transform (CWT)-based method was developed in which parts of the scalogram that have been affected by artefact correction are excluded from power calculations. The method was evaluated by simulating artefact correction on HRV data that were originally free of artefacts. Commonly used spectral HRV parameters were calculated by the developed method and by the short-time Fourier transform (STFT), which was used as a reference. Except for the powers in the very low-frequency and low-frequency (LF) bands, powers calculated by the STFT proved to be extremely sensitive to artefact correction. The CWT-based calculations in the high-frequency and very high-frequency bands corresponded well with their theoretical values. The standard deviations of these powers, however, increase with the number of corrected artefacts which is the result of the non-stationarity of the R–R interval series that were analysed. The powers calculated in the LF band turned out to be slightly sensitive to artefact correction, but the results were acceptable up to 20% artefact correction. Therefore, the CWT-based method provides a valuable alternative for the analysis of HRV data that cannot be guaranteed to be free of artefacts.