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An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis

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Advanced Analytics and Learning on Temporal Data (AALTD 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11986))

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Abstract

This paper describes an initial investigation on adapting windowed Dynamic Time Warping (DTW) for enhancing the reliability of fast DTW for Electrocardiogram analysis in Cardiology, a domain where risks are especially important to avoid. The key question it explores is whether it is worthwhile to adapt the window size of DTW for every query temporal sequence, a factor critically determining the speed-accuracy tradeoff of DTW. It in addition extends the adaptation to cover also the order of sequences for lower bound calculations. Experiments on ECG temporal sequences show that the techniques help significantly reduce risks that windowed DTW algorithms are subject to and at the same time keeping a high speed.

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Shen, D., Chi, M. (2020). An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis. In: Lemaire, V., Malinowski, S., Bagnall, A., Bondu, A., Guyet, T., Tavenard, R. (eds) Advanced Analytics and Learning on Temporal Data. AALTD 2019. Lecture Notes in Computer Science(), vol 11986. Springer, Cham. https://doi.org/10.1007/978-3-030-39098-3_16

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  • DOI: https://doi.org/10.1007/978-3-030-39098-3_16

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  • Print ISBN: 978-3-030-39097-6

  • Online ISBN: 978-3-030-39098-3

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