| Project/Area Number |
16K12513
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Kansei informatics
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| Research Institution | Hiroshima University |
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Principal Investigator |
Tsuji Toshio 広島大学, 工学研究科, 教授 (90179995)
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| Co-Investigator(Kenkyū-buntansha) |
吉田 将之 広島大学, 生物圏科学研究科, 准教授 (70253119)
平野 旭 呉工業高等専門学校, 電気情報工学分野, 准教授 (60594778)
曽 智 広島大学, 工学研究科, 助教 (80724351)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 小型魚類 / 感性計測評価 / 生体信号計測 / 行動計測 / 感性情報学 |
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| Outline of Final Research Achievements |
In this study, we developed a system that can measure bioelectric signals of zebrafish called ventilatory signals and enable estimation of the swimming position and velocity from the measured ventilatory signals with the equivalent accuracy as a video-analysis system, and proposed a method to estimate the affective state of a zebrafish in the combination of the evaluation indices related to ventilation and motion. Experiments were conducted to induce unpleasant and pleasant states using alarm substances and ethanol, respectively, and found that the induced affective states can be expressed on the axes composed of evaluation indices and can be estimated from the evaluation indices using our original classifier called Log-Linearized Gaussian Mixture Network. Finally, a method to predict the transition of the affective state and estimation of the start time of habituation in zebrafish was also proposed.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究成果は魚の心理・感性を定量評価するための新たな方法論を提案するものであり，『生物感性工学』という世界初の学術分野の創出につながる可能性がある．これまで詳細に解析されていなかった快状態の検出を可能にしたことから，本研究成果は情動分化という進化論上の問題を解決するための糸口となり得るだけでなく，魚の心理状態モニタリングによるヒトと飼育魚の間のコミュニケーションシステムという社会実装への展開も期待できる．さらに，本研究で提案した魚の情動状態推定法は，ゼブラフィッシュの行動を評価することにより薬効検証を行っている創薬分野にも応用できる可能性がある．
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