A comparison of actual and artifactual features based on fractal analyses: Resting-State MEG data

Montri Phothisonothai, Hiroyuki Tsubomi, Aki Kondo, Yuko Yoshimura, Mitsuru Kikuchi, Yoshio Minabe, Katsumi Watanabe

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Future standardized system for distinguishing actual and artifactual magnetoencephalogram (MEG) data is an essential tool. In this paper, we proposed the quantitative parameters based on fractal dimension (FD) analyses in which the FD may convey different features before and after artifact removal. The six FD algorithms based on time-series computation, namely, box-counting method (BCM), variance fractal dimension (VFD), Higuchi's method (HM), Kazt's method (KM), detrended fluctuation analysis (DFA), and modified zero-crossing rate (MZCR) were compared. These approaches measure nonlinear-behavioral responses in the resting-state MEG data. Experimental results showed that the FD value of actual MEG was increased statistically in comparison with the artifactual MEG. The DFA and the HM present a best performance for analyzing simulated data and resting-state MEG data, respectively.

Original languageEnglish
Title of host publicationProceedings of The Eighth International Conference on Bio-Inspired Computing
Subtitle of host publicationTheories and Applications (BIC-TA), 2013
PublisherSpringer Verlag
Pages1257-1265
Number of pages9
ISBN (Print)9783642375019
DOIs
Publication statusPublished - 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume212
ISSN (Print)2194-5357

Keywords

  • Artifact removal
  • Complexity measure
  • Fractal dimension
  • MEG
  • Nonlinear analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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    Phothisonothai, M., Tsubomi, H., Kondo, A., Yoshimura, Y., Kikuchi, M., Minabe, Y., & Watanabe, K. (2013). A comparison of actual and artifactual features based on fractal analyses: Resting-State MEG data. In Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013 (pp. 1257-1265). (Advances in Intelligent Systems and Computing; Vol. 212). Springer Verlag. https://doi.org/10.1007/978-3-642-37502-6_146