Wakayama University · Faculty of Systems Engineering · 助教

Research keywords音響工学, 音質評価, 聴覚, 生体信号解析, 心理音響

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• Deep Learning-Based Estimating Magnitude of Acoustic Fluctuation from Event-Related Potentials for Objective Assessment of Attentional States2026
• 2025年度自動車技術会 大学院研究奨励賞2025 · 2026年03月 自動車技術会
• Effect of changes in vehicle sound on attentional mechanisms and event-related potentials2025 · Yuki Kameyama, Hirona Murakami, Shunsuke Ishimitsu, Keisuke Kotaka, Yasuto Fujii (担当区分： 筆頭著者 )
• Evaluating attentional responses to electric vehicle driving noise through event-related potentials: a frequency bands analysis2024 · The advent of electric vehicles (EVs), known for their quieter operation compared to Internal Combustion Engine (ICE) vehicles, has shifted auditory attention towards wind and road noise. This shift is further accentuated by the anticipated future dominance of autonomous vehicles, which is expected to reduce the cognitive demands of driving, potentially heightening sensitivity to external noise and leading to increased annoyance and discomfort. This research investigates the impact of driving noise on selective attention by identifying sounds that significantly disrupt adaptation to driving noise through the analysis of event-related potentials (ERPs). Unlike previous studies that concentrated on the peak high-frequency driving noise fluctuations around 1000 Hz, our study explores a broader spectrum of higher frequencies. By recording brain responses to driving-related auditory stimuli, we detected variations in ERPs across different frequency bands, thereby pinpointing the acoustic characteristics most disruptive to concentration. Our findings aim to contribute towards enhancing driver focus and improving the acoustic comfort inside vehicle cabins.

• 2022年度最優秀修士論文, 広島市立大学大学院情報科学研究科システム工学専攻
• 学長奨励賞, 広島市立大学
• 2020年度優秀卒業論文, 広島市立大学情報科学部システム工学科

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