TY - CHAP
T1 - A comparison of actual and artifactual features based on fractal analyses
T2 - Resting-State MEG data
AU - Phothisonothai, Montri
AU - Tsubomi, Hiroyuki
AU - Kondo, Aki
AU - Yoshimura, Yuko
AU - Kikuchi, Mitsuru
AU - Minabe, Yoshio
AU - Watanabe, Katsumi
N1 - Funding Information:
This research was supported by the Japan Society for the Promotion of Science (JSPS) and the Hokuriku Innovation Cluster for Health Science (MEXT Program for Fostering Regional Innovation).
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Artifact removal
KW - Complexity measure
KW - Fractal dimension
KW - MEG
KW - Nonlinear analysis
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U2 - 10.1007/978-3-642-37502-6_146
DO - 10.1007/978-3-642-37502-6_146
M3 - Chapter
AN - SCOPUS:84880358305
SN - 9783642375019
T3 - Advances in Intelligent Systems and Computing
SP - 1257
EP - 1265
BT - Proceedings of The Eighth International Conference on Bio-Inspired Computing
PB - Springer Verlag
ER -