Variability analysis of epileptic EEG using the maximal overlap discrete wavelet transform

Abstract

Purpose

To determine if there is a difference in the wavelet variances of seizure and non-seizure channels in the EEG of an epileptic subject.

Methods

A six-level decomposition was applied using the Maximal Overlap Discrete Wavelet Transform (MODWT). The wavelet variance and 95% CIs were calculated for each level of the decomposition. The number of changes in variance for each level were found using a change-point detection method of Whitcher. The Kruskal–Wallis test was used to determine if there were differences in the median number of change points within channels and across frequency bands (levels).

Results

No distinctive pattern was found for the wavelet variances to differentiate the seizure and non-seizure channels. The seizure channels tended to have lower variances for each level and overall, but this pattern only held for one of the three seizure channels (RAST4). The median number of change points did not differ between the seizure and non-seizure channels either within each channel or across the frequency bands.

Conclusion

The use of the MODWT in examining the variances and changes in variance did not show specific patterns which differentiate between seizure and non-seizure channels.

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Fig. 1

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Acknowledgements

We thank Dr. Giridhar Kalamangalam for providing the data in this study.

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Correspondence to Dejian Lai.

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Follis, J.L., Lai, D. Variability analysis of epileptic EEG using the maximal overlap discrete wavelet transform. Health Inf Sci Syst 8, 26 (2020). https://doi.org/10.1007/s13755-020-00118-4

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Keywords

  • EEG
  • Epilepsy
  • Kruskal–Wallis test
  • Wavelet transformation
  • Whitcher test