Two-dimensional Motif Extraction from Images: A Study using an Electrocardiogram

Aldosari, Hanadi, Coenen, Frans ORCID: 0000-0003-1026-6649, Lip, Gregory ORCID: 0000-0002-7566-1626 and Zheng, Yalin ORCID: 0000-0002-7873-0922
(2022) Two-dimensional Motif Extraction from Images: A Study using an Electrocardiogram. In: 14th International Conference on Knowledge Discovery and Information Retrieval, 2022-10-24 - 2022-10-26.

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A mechanism using the concept of 2D motifs to classify Electrocardiogram (ECG) data is presented. The motivation is that existing techniques typically first transform ECG data into a 1D signal (waveform) format and then extract a small number of features from this format for classification purposes. The transformation into the waveform format introduces an approximation of the data, and the consequent feature selection means that only a small part of the coarsened signal is utilised. The proposed approach works directly with the image format, no transformation takes place, features (motifs) are selected by considering the entire ECG image. It is argued that this produces a better classification than that which can be achieve using the waveform format. The proposed 2D Motif extraction approach is fully described and evaluated. Good results are returned, a best accuracy 85% in comparison with a best accuracy of 70% using a comparable 1D waveform approach. An analysis is also presented with respect to the augmentation of 2D motifs with 2D discords.

Item Type: Conference or Workshop Item (Unspecified)
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences
Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 15 Mar 2023 10:16
Last Modified: 15 Mar 2024 01:02
DOI: 10.5220/0011380500003335
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