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The International Conference on Artificial Intelligence and Applied Mathematics in Engineering

ICAIAME 2019: Artificial Intelligence and Applied Mathematics in Engineering Problems pp 47–56Cite as

Feature Extraction of Hidden Oscillation in ECG Data via Multiple-FOD Method

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Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 43))

Abstract

Fourier transform (FT) is a non-parametric method which can be used to convert the time domain data into the frequency domain and can be used to find the periodicity of oscillations in time series datasets. In order to detect periodic-like outliers in time series data, a novel and promising method, named as the outlier detection via Fourier transform (FOD), has been developed. From our previous studies, it has been shown that FOD outperforms most of the commonly used approaches for the detection of outliers when the outliers have periodicity with low fold changes or high sample sizes. Recently, the multiple oscillation and hidden periodic-like pattern cases for time series data have been investigated and found that the multiple application of FOD, shortly multiple-FOD, can also be a successful method in the detection of such patterns. These empirical results are based on real electrocardiogram (ECG) data where the discrimination of disorders can be helpful for the diagnosis of certain heart diseases in advance. Hereby, in this study, we evaluate the performance of multiple-FOD in different types of simulated datasets which have distinct sample sizes, percentage of outliers and distinct hidden patterns.

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Author information

Authors and Affiliations

  1. Biomedical Engineering, Middle East Technical University, 06800, Ankara, Turkey

    Ekin Can Erkuş & Vilda Purutçuoğlu

  2. Department of Statistics, Middle East Technical University, 06800, Ankara, Turkey

    Vilda Purutçuoğlu

Authors
  1. Ekin Can Erkuş
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  2. Vilda Purutçuoğlu
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Corresponding author

Correspondence to Vilda Purutçuoğlu .

Editor information

Editors and Affiliations

  1. Department of ECE, Karunya University, Coimbatore, Tamil Nadu, India

    D. Jude Hemanth

  2. Department of Computer Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Isparta, Turkey

    Utku Kose

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Erkuş, E.C., Purutçuoğlu, V. (2020). Feature Extraction of Hidden Oscillation in ECG Data via Multiple-FOD Method. In: Hemanth, D., Kose, U. (eds) Artificial Intelligence and Applied Mathematics in Engineering Problems. ICAIAME 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 43. Springer, Cham. https://doi.org/10.1007/978-3-030-36178-5_5

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