Fast computation of spectral centroids |
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Authors: | Melody L Massar Matthew Fickus Erik Bryan Douglas T Petkie Jr" target="_blank">Andrew J TerzuoliJr |
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Institution: | (1) Department of Management Systems Engineering, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan;(2) Self Defense Force Central Hospital, Japan Ground Self-Defense Force, Ikejiri 1-2-24, Setagaya, Tokyo 154-0001, Japan;(3) Division of Biomedical Engineering, National Defense Medical College, Research Institute, Namiki 3-2, Tokorozawa Saitama, 359-8513, Japan; |
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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. |
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