Stationarity of the EEG Segment with Event-Related Potentials

Gai Ling Fan; Zhi Hua Huang

doi:10.4028/www.scientific.net/AMM.148-149.30

Paper Titles

Punch Force Analysis in the Forming of "U" Clamps by Using Combination Die
p.11

Studies of Optimum Conditions for Cross-Linking Immobilization of Alkaline Protease on Graphene Oxide
p.15

Investigation on Temperature Field and Thermal Stress of Dish Solar Concentrator’s Focal Region
p.20

Influence of Precracked Diffusion Coating of Pt-Modified Aluminide on HCF Fracture Mechanism of IN 792 Nickel-Based Superalloy
p.24

Stationarity of the EEG Segment with Event-Related Potentials
p.30

Study on Growth of Oxide Scale on High Carbon Steel at High Temperature
p.34

Research on Fluorescence Imaging Detecting System of Intracellular Calcium
p.38

The Design of Promoting and Thrust Gear on Refrigerator Body
p.42

Isolation and Characterization of a Sulfanilic Acid Degrading Bacterial Strain
p.46

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 148-149Stationarity of the EEG Segment with Event-Related...

Stationarity of the EEG Segment with Event-Related Potentials

Abstract:

EEG (electroencephalography), as a noninvasive and inexpensive method, is widely used to measure brain function and make inferences about regional brain activity. The stationarity of EEG has been investigated by many researchers, while the stationarity of EEG segment with ERPs (Event-related Potentials) has hardly been concerned about. It is necessary to analyze the stationarity of this kind of EEG. In this paper, we concentrate on the stationarity of the EEG with ERPs by testing the stationarity of 500ms EEG segments with ERPs recorded from six subjects in two types of experiments. The results suggest that selected EEG segment whose length is larger than 190ms remains to be stationarity and all epochs duration less than 40ms is considered to be stationary, whichever channel the data is from and whatever type of cognitive task is performed in the experiment. This is an obvious difference between the stationarity of EEG with ERPs and that of EEG, which is reported to be stationary as long as its length is less than 12s.

You might also be interested in these eBooks

Mechanical Engineering, Materials and Energy

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 148-149)

Pages:

30-33

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.148-149.30

Citation:

Cite this paper

Online since:

December 2011

Authors:

Gai Ling Fan, Zhi Hua Huang

Keywords:

EEG, Enterprise Resource Planning (ERP), Run Test, Stationarity

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] N. Burch, W. Nettleton, J. Sweeney: Period analysis of the electroencephalogram on a general-purpose digital computer. Ann. N. Y. Acad. Sci. 115, 827-843 (1964).

DOI: 10.1111/j.1749-6632.1964.tb00061.x

Google Scholar

[2] N. Kawabata: A Nonstationary analysis of the electroencephalogram. IEEE Trans. Biodmed. Engineering BME-20, 444-452 (1973).

DOI: 10.1109/tbme.1973.324218

Google Scholar

[3] T. Inouye, S. Toi, Y. Matsumoto: A new segmentation method of electroencephalograms by use of Akaike's information criterion. Cogn. Brain Res. 3, 33-40 (1995).

DOI: 10.1016/0926-6410(95)00016-x

Google Scholar

[4] R.Q. Quiroga, H. Garcia: Single-trial event-related potentials with wavelet denoising. Clinical Neurophysiology, 114, 376-390 (2003).

DOI: 10.1016/s1388-2457(02)00365-6

Google Scholar

[5] P. Lyyra, J. Wikgren, and P. Astikainen: Event-related potentials reveal rapid registration of features of infrequent changes during change blindness. Behavioral and brain functions BBF Volume 6, 12 pages (2010).

DOI: 10.1186/1744-9081-6-12

Google Scholar

[6] N. Williams, S.J. Nasuto, J.D. Saddy: Evaluation of EmpiricalMode Decomposition for Event-Related Potential Analysis. Journal on Advances in Signal Processing Volume (2011).

DOI: 10.1155/2011/965237

Google Scholar

[7] J.S. Bendat, A.G. Piersol: Random data: analysis and measurement procedures. Wiley-Interscience, New York (1971).

DOI: 10.1177/058310247400600707

Google Scholar

[8] B. Saltzberg: Theoretical and experimental investigations of electroencephalographic signals using parameter tracking and matched digital filtering. Doctoral Dissertation, Marquette University, Milwaukee (1972).

Google Scholar

[9] H. Berger: Archive Psychiatryscher Nervenkrankheiten. Arch. Psychiatr. Nervenkr. 87, 527-570 (1929).

Google Scholar

[10] B.A. Cohen, A. Sances: Stationarity of the human electroencephalogram. Med. Biol. Eng. Comput. 15, 513-518 (1977).

DOI: 10.1007/bf02442278

Google Scholar

[11] W.C. Schefler: Statistics for the biological sciences. Addison-Wesley, Boston (1969).

Google Scholar