Quantifying morphology changes in time series data with skew
Name
Sung-2009-QUANTIFYING MORPHOLOGY CHANGES IN TIME SERIES DATA WITH SKEW.pdf
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125.95 KB
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Adobe PDF
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Author(s)
Sung, Phil
Syed, Zeeshan
Guttag, John V.
Date Issued
April 2009
Journal
ICASSP (IEEE International Conference on Acoustics, Speech and Signal Processing)
Publisher
Institute of Electrical and Electronics Engineers
Citation
Sung, P., Z. Syed, and J. Guttag. “Quantifying Morphology Changes in Time Series Data with Skew.” Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference On. 2009. 477-480. Copyright © 2009, IEEE
Version
Final published version
Abstract
This paper examines strategies to quantify differences in the morphology of time series while accounting for time skew in the observed data. We adapt four measures originally designed for signal shape comparison: Dynamic Time-Warping (DTW), Earth Mover's Distance (EMD), Frochet Distance (FD), and Hausdorff Distance (HD). These morphology difference metrics on time series are compared in discriminative power and noise resistance on ECG signals as well as on a synthetic dataset. We use data from our experiments to shed light on the relative strengths of the methods.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/ICASSP.2009.4959624
