Fast Computation of Spectral CentroidsAdvances in Computational Mathematics
AbstractThe spectral centroid of a signal is the curve whose value at any given time is the centroid of the corresponding constant-time cross section of the signal’s spectrogram. A spectral centroid provides a noise-robust estimate of how the dominant frequency of a signal changes over time. As such, spectral centroids are an increasingly popular tool in several signal processing applications, such as speech processing. We provide a new, fast and accurate algorithm for the real-time computation of the spectral centroid of a discrete-time signal. In particular, by exploiting discrete Fourier transforms, we show how one can compute the spectral centroid of a signal without ever needing to explicitly compute the signal’s spectrogram. We then apply spectral centroids to an emerging biometrics problem: to determine a person’s heart and breath rates by measuring the Doppler shifts their body movements induce in a continuous wave radar signal. We apply our algorithm to real-world radar data, obtaining heart- and breath-rate estimates that compare well against ground truth.
Citation InformationMelody L. Massar, Matthew Fickus, Erik Bryan, Douglas T. Petkie, et al.. "Fast Computation of Spectral Centroids" Advances in Computational Mathematics Vol. 35 Iss. 1 (2011) p. 83 - 97 ISSN: 10197168
Available at: http://works.bepress.com/douglas_petkie/75/