Detection of P300 brain waves using a MagnetoImpedance sensor

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 7 , ISSUE 5 (December 2014) > List of articles

Special issue ICST 2014

Detection of P300 brain waves using a MagnetoImpedance sensor

K. Wang * / S. Tajima / Y. Asano / Y. Okuda / N. Hamada / C. Cai / T. Uchiyama

Keywords : Biomagnetic field measurement; Magneto-Impedance sensor; MEG; P300 brain waves

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 5, Pages 1-4, DOI: https://doi.org/10.21307/ijssis-2019-087

License : (CC BY-NC-ND 4.0)

Published Online: 15-February-2020

ARTICLE

ABSTRACT

We have previously reported a study on brain activity detection in occipital region using a picotesla-scale MagnetoImpedance (MI) sensor. Based on past studies, the target of the present study was to review the performance of MI sensor on parietal region brain activity detection. Human brain magnetic field is extremely weak, in order to detect the faint magnetic field, we constructed an MI measurement system that can cancel out the background noise (e.g., geomagnetic field) instead of using a magnetic shielding. In this study, we recorded P300 brain waves of subjects, compared our results with our past studies and other EEG and MEG data reported previously. The results confirmed the reliability of our data and indicated that the MI sensor can be applied on brain activity detection.

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REFERENCES

[1] Luck, Steven J. (2005), “An Introduction to the Event-Related Potential Technique,”  The MIT Press. ISBN 0-262-12277-4.

[2] Polich, J. (2007), “Updating P300: An integrative theory of P3a and P3b,” Clinical Neurophysiology, 118(10), 2128-2148.

[3] Squires, N.K., Squires, K.C., & Hillyard, S.A. (1975), “Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in man,” Electroencephalography & Clinical Neurophysiology, 38, 387-401.

[4] T. Uchiyama, K. Mohri, Y.Honkura, and L.V. Panina, “Recent advances of pico-Tesla resolution Magneto-Impedance Sensor based on amorphous wire CMOS IC MI Sensor,” IEEE Transactions on magnetics, VOL. 48, NO. 11, NOVEMBER 2012.

[5]  J. Polich ,and C.Margala, “P300 and probability: comparison of oddball and single-stimulus paradigms,” International Journal of Psychophysiology 25 (1997)169-176.

[6] S. Tajima, T. Uchiyama, Y. Okuda, and K. Wang,“Brain activity measurement in the occipital region of the head using a magnetoimpedance sensor,” 2013 Seventh International Conference on Sensing Technology (ICST), 267-270.

[7] J.Y. Bennington, and J.Polich, “Comparison of P300 from passive and active tasks for auditory and visual stimuli,” International Journal of Psychophysiology 34 (1999) 171-177.

[8] A. Mecklinger, B. Maess, B. Opitz, E. Pfeifer, D. Cheyne,and H. Weinberg, “A MEG analysis of the P300 in visual discrimination tasks,” Electroencephalography and clinical Neurophysiology 108 (1998) 45– 56.

[9] C. Bledowski, D.Prvulovic, R.Goebel, F.E.Zanella, and D.E.J.Linden, “Attentional systems in target and distractor processing: a combined ERP and fMRI study,” NeuroImage 22 (2004) 530– 54.

[10] Matti Hämäläinen, Riitta Hari, Risto J. Ilmoniemi, Jukka Knuutila, and Olli V. Lounasmaa, “Magnetoencephalography, theory,instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413 – Published 1 April 1993

[11] T. maeno, A. kaneko, K. Iramina, F. Eto, and S. Ueno, “Source modeling of the P300 event-related response using magnetoencephalography and electroencephalography measurements,” IEEE TRANSACTIONS ON MAGNETICS, VOL. 39, NO. 5, SEPTEMBER 2003.

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