EEG Variations During Measurement of Cognitive Functions Using Biosignal Acquisition Toolkit

Yoshio Kaji; Yoshikazu Yamamoto; Junji Kawata; Jiro Morimoto; Shoichiro Fujisawa

doi:10.20965/jrm.2020.p0753

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JRM Vol.32 No.4 pp. 753-760

doi: 10.20965/jrm.2020.p0753

(2020)

Paper:

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EEG Variations During Measurement of Cognitive Functions Using Biosignal Acquisition Toolkit

Yoshio Kaji, Yoshikazu Yamamoto, Junji Kawata, Jiro Morimoto, and Shoichiro Fujisawa

Faculty of Science and Engineering, Tokushima Bunri University
1314-1 Shido, Sanuki, Kagawa 769-2193, Japan

Received:

January 1, 1970

Accepted:

June 26, 2020

Published:

August 20, 2020

Keywords:

electroencephalogram (EEG), brain function, cognitive function, biosignal acquisition toolkit, spectral analysis

Abstract

The occurrence of serious traffic accidents due to driving error has recently become a social issue. The decline in cognitive functions is considered a factor particularly among elderly drivers, for which some corrective measures are urgently needed. Currently, as a measure dealing with elderly drivers, drivers aged 75 years are required by law to examine their cognitive functions when they renew their driver’s license. This examination is conducted to measure memory and power of judgment. In the present study, we used a device that allows simple measurements and attached electrodes to the frontal pole, where it is easy to attach; measure electroencephalograms for the cognitive functions of memory, mental calculations (thinking), and memory recall; and examine the changes in the power spectra to determine how they vary in young and elderly individuals.

An example of analysis (mental calculation)

Cite this article as:

Y. Kaji, Y. Yamamoto, J. Kawata, J. Morimoto, and S. Fujisawa, “EEG Variations During Measurement of Cognitive Functions Using Biosignal Acquisition Toolkit,” J. Robot. Mechatron., Vol.32 No.4, pp. 753-760, 2020.

Data files:

References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] J. Takanashi, “Electroencephalography of dementia,” Japanese J. of Medical Technology, Vol.66, Issue J-STAGE-2, pp. 55-61, 2017 (in Japanese).

[2] [2] H. Mori, I. Horiguchi, and T. Shimizu, “Evaluation of Depressive State With Pre-Frontal Electroencephalographic Spectra,” Juntendo Medical J., Vol.59, Isuue 3, pp. 267-272, 2013 (in Japanese).

[3] [3] S. Ito, Y. Mitsukura, M. Fukumi, and N. Akamatsu, “Proposal of the EEG Analysis Method Using the Individual Characteristic of the EEG,” IEEJ Trans. EIS, Vol.124, No.6, pp. 1259-1266, 2004 (in Japanese).

[4] [4] Y. Kohata, Y. Mitsukura, M. Shinozuka, S. Yamamoto, and H. Funamori, “An Air Environment Evaluation Using Electroencephalogram (EEG),” Techinical Papers of Annual Meeting the Society of Heating, Air-conditioning and Sanitary Engineers of Japan, pp. 141-144, 2018 (in Japanese).

[5] [5] D. Takehara, H. Kayanuma, M. Matsubara, N. Seki, K. Wada, M. Kurata, and Y. Ono, “Development of an ERD measurement system using Emotiv Epoc,” Trans. of Japanese Society for Medical and Biological Engineering, Vol.55, pp. 556-559, 2017 (in Japanese).

[6] [6] T. Sasaki, Y. Akimoto, and K. T. Nakahira, “Evaluation of Brain Responses Reflecting Differences in Difficulty of English Word Recognition by Using Low-cost Electroencephalograph,” Trans. of Japanese Society for Information and Systems in Education, Vol.36, Issue 2, pp. 149-153, 2019 (in Japanese).

[7] [7] H. Kishima, T. Yanagisawa, H. M. Khoo, and K. Edakawa, “The Current Status and Future Application of Research in Brain Function,” Jpn. J. Neurosurg, Vol.26, No.12, pp. 892-897, 2017 (in Japanese).

[8] [8] T. Hidaka, Y. Shiraishi, Y. Kawai, and J. Okuda, “Information Control System Based on EEG Using Smartphone,” Proc. of IPSJ Interaction 2014, pp. 480-485, 2014 (in Japanese).

[9] [9] S. Shimizu and H. Inoue, “Basic Study for New Assistive System Based on Brain Activity during Car Driving,” Japanese J. of Cognitive Neuroscience, Vol.15, No.1, pp. 41-46, 2013 (in Japanese).

[10] [10] J. Chen, D. Jiang, and Y. Zhang, “A Common Spatial Pattern and Wavelet Packet Decomposition Combined Method for EEG-Based Emotion Recognition,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.2, pp. 274-281, 2019.

[11] [11] Y. Mizuno-Matsumoto, Y. Tanaka, T. Hayashi, E. Okamoto, H. Nishimura, and H. Inada, “An Analysis of EEG and Plethysmogram on Working Environment under Mental Workload,” Trans. of Japanese Society for Medical and Biological Engineering, Vol.48, No.1, pp. 11-24, 2010 (in Japanese).

[12] [12] S. Miyazaki, “Pulse-wave based emergency alarm system for the living alone elderly: A feasibility study,” J. of the Society of Biomechanisms, Vol.26, No.1, pp. 32-39, 2002 (in Japanese).

[13] [13] Y. Kaji, M. Akutagawa, F. Shichijo, Y. Kinouchi and S. Nagahiro, “Development of Real-time Intra – operative Analysis Software for Brain Activity Using Measured EEG,” Trans. of Japanese Society for Medical and Biological Engineering, Vol.42, No.2, pp. 41-47, 2004 (in Japanese).

[14] [14] M. Yamazaki and M. Matsuura, “EEG in adults and elderly,” Japanese J. of Clinical Neurophysiology, Vol.42, Issue 6, pp. 387-392, 2014 (in Japanese).