Researcher Information - KURIHARA Yousuke |

（Last updated : 2025-08-01 20:34:41）

KURIHARA Yousuke

Department / Course

Aoyama Gakuin University College of Science and Engineering 経営システム工学科

Job Professor

Specialization and related fields
Control and system engineering, Measurement engineering

Business career
1.	2013/04/01 ～ 2019/03/31	Associate Professor Aoyama Gakuin University College of Science and Engineering Department of Industrial and Systems Engineering
2.	2019/04/01 ～	Professor Aoyama Gakuin University College of Science and Engineering Department of Industrial and Systems Engineering

Book and thesis
1.	Books	Gerontology as an Interdisciplinary Science, Part I Chapter 2, Unconstrained Biosignal Measurement Technology and Its Applications in Assisting Aged Society 2024/07
2.	Books	ヒューマンロボティクス神経メカニクスと運動制御 2017/09
3.	Books	Tele-Healthcare Computing and Engineering: Principles and Design (edited by Fei Hu),pp.325-340 (Co-authored) 2013/04
4.	Papers	"Fan Pressurization Method to Measure House Leakage Area Using Built-in Exhaust Fans and Window Openings as Reference Areas," IEEE Sensors Journal (In press) (Co-authored) 2025/08
5.	Papers	"Numerical Integration Error in Linear Ordinary Differential Equations—Characteristic Root Distortion by Integration," IEEE Access, vol. 13, pp. 66188-66196, (Apr. 2025) (Co-authored) 2025/04
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Academic conference presentation
1.	2025/03/29	Proposal for a Method to Classify Fabricated Responses Using a Psychological Bias Loading Model Based on Factor Analysis of EEG During NEO-FFI Responses (The 13th IIAE International Conference on Industrial Application Engineering 2025)
2.	2025/03/19	Proposal for a Method for Classify Fabricated Responses Caused by Psychological Biases Using Brain Activity Networks Based on Granger Causality in EEG Responses to the NEO-FFI” (The International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making 2025 (IUKM 2025))
3.	2025/01/23	Proposal of a Brain Activation Five–Layer Network with Five Types of EEG for Classification of Artificial Responses in NEO-FFI by Utilizing Graph Fourier Transform (30th International Symposium on Artificial Life and Robotics)
4.	2024/12/04	A Method for Classification NEO–FFI Answers Fabricated and Advantageous due to Psychological Bias Using Brainwave Specific Brain Activity Networks (2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC))
5.	2024/08/30	Detecting of Deliberate Responses due to Social Desirability Bias in Multiple-Choice-Based Personality Tests Using Occipital Lobe EEG Beta Wave Content Rates (2024 63rd Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE))
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