2022 Fiscal Year Final Research Report
Prediction of dynamic food texture sensation by multimodal sensory integration and dominant model
| Project/Area Number |
20K12026
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 61060:Kansei informatics-related
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| Research Institution | Kobe University |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | 食感計測 / 多感覚情報処理 |
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| Outline of Final Research Achievements |
This study proposed a multisensory integration model that predicts the degree of food texture from the senses of tactile and hearing. The model is a Gaussian process model. Explanatory variables were feature values determined from the force, vibration, and sound data in food breakage. Objective variables were the sensory evaluation values of food textures such as saku-saku. This study verified that the model predicted the sensory evaluation values within a 5% error of the range of evaluation values through experiments. This study also proposed a state space model to predict a dominant sensation from measurement data and previous sensations. We confirmed the effectiveness of the model through laboratory experiments.
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| Free Research Field |
計測工学
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| Academic Significance and Societal Importance of the Research Achievements |
多感覚統合によって食感を推定する方法は食感推定において新たなアプローチであり，インパクトも高い．また，時間変化を伴う支配的食感についても挑戦的な試みであり，咀嚼の開始から嚥下までの過程を対象とするOral processingの考え方に沿っている．いずれも食感を推定する新たな方法を提案できた．食感は固形食品のおいしさを決定する需要な要素とされており，食品開発においても評価のニーズがある．本研究の成果を，食感の定量化のニーズをもつ企業への技術移転を進めたい．
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