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Continuous biological signals, like blood pressure recordings, exhibit nonlinear and nonstationary properties which must be considered during their analysis. Heart rate variability analyses have identified several frequency components and their autonomic origin. There is need for more knowledge on the time-changing properties of these frequencies. The power spectrum, continuous wavelet transform and Hilbert-Huang transform are applied on a continuous blood pressure signal to investigate how the different methods compare to each other. The Hilbert-Huang transform shows high ability to analyze such data, and can, by identifying instantaneous frequency shifts, provide new insights into the nature of these kinds of data.