Quantifying morphology changes in time series data with skew
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), a...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers
2011
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| Online Access: | http://hdl.handle.net/1721.1/62155 https://orcid.org/0000-0003-0992-0906 |
| Summary: | 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. |
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