Fast computation of spectral centroids
Document Type
Article
Publication Date
6-8-2010
Abstract
The 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.
Source Publication
Advances in Computational Mathematics (ISSN 1019-7168 | eISSN 1572-9044)
Recommended Citation
Massar, M.L., Fickus, M., Bryan, E. et al. Fast computation of spectral centroids. Adv Comput Math 35, 83–97 (2011). https://doi.org/10.1007/s10444-010-9167-y
Comments
Copyright © 2010, Springer Science Business Media, LLC
The full article is accessible by subscription or purchase at the DOI link below.
Co-author M. Massar was an AFIT PhD student at the time of this paper. (href="https://scholar.afit.edu/etd/1194/"">AFIT-DAM-ENC-12-02, March 2012)