A consensus algorithm for approximate string matching and its application to QRS complex detection

Alfonso Alba (), Martin O. Mendez (), Miguel E. Rubio-Rincon and Edgar R. Arce-Santana
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Alfonso Alba: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Salvador Nava Mtz. S/N, Zona Universitaria, 78290, San Luis Potosí, SLP, México
Martin O. Mendez: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Salvador Nava Mtz. S/N, Zona Universitaria, 78290, San Luis Potosí, SLP, México
Miguel E. Rubio-Rincon: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Salvador Nava Mtz. S/N, Zona Universitaria, 78290, San Luis Potosí, SLP, México
Edgar R. Arce-Santana: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Salvador Nava Mtz. S/N, Zona Universitaria, 78290, San Luis Potosí, SLP, México

International Journal of Modern Physics C (IJMPC), 2016, vol. 27, issue 03, 1-13

Abstract: In this paper, a novel algorithm for approximate string matching (ASM) is proposed. The novelty resides in the fact that, unlike most other methods, the proposed algorithm is not based on the Hamming or Levenshtein distances, but instead computes a score for each symbol in the search text based on a consensus measure. Those symbols with sufficiently high scores will likely correspond to approximate instances of the pattern string. To demonstrate the usefulness of the proposed method, it has been applied to the detection of QRS complexes in electrocardiographic signals with competitive results when compared against the classic Pan-Tompkins (PT) algorithm. The proposed method outperformed PT in 72% of the test cases, with no extra computational cost.

Keywords: Approximate string matching; consensus measure; QRS complex; pattern recognition (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1142/S0129183116500297

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