In January 2018, a cooperation between Signal Analysis Lab, St. Olav's University Hospital, and NTNU led to the paper "Instantaneous Frequencies of Continuous Blood Pressure a Comparison of the Power Spectrum, the Continuous Wavelet Transform and the Hilbert–Huang Transform" in Advances in Data Science and Adaptive Analysis. It is written by Kathrine Knai, Signal Analysis Lab employee Geir Kulia, Dr Nils Kristian Skjærvold, and Professor Marta Molinas.


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 analyse such data, and can, by identifying instantaneous frequency shifts, provide new insights into the nature of these kinds of data.

The paper can be read here.