2019
DOI: 10.18494/sam.2019.2353
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Food Texture Estimation Using Robotic Mastication Simulator Equipped with Teeth and Tongue

Abstract: In this paper, we propose a food texture estimation system using a robotic mastication simulator equipped with teeth and a tongue. On the basis of the human oral function, we first introduce the mastication robot with which we can measure biting force and tongue pressure simultaneously during artificial mastication. We then develop a texture estimation system that estimates the value of human sensory evaluation from feature values of measured data. Finally, we describe an experiment where textures of doughnuts… Show more

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Cited by 10 publications
(1 citation statement)
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“…Several artificial oral systems have been developed and further improvements to simulate masticatory motion for observing chewing trajectory and its physiological constraints [16]. These models include measuring chewing force and jaw movement related to the physical properties of food [17], simulating bolus formation using a cylindrical chamber driven by a flat mechanical plunger [18], and assessing food texture using a robotic simulator [19]. In these models, focused on reproducing the chewing action and trajectory, it is still difficult to explain the volatile compounds released from different foods during mastication.…”
Section: Introductionmentioning
confidence: 99%
“…Several artificial oral systems have been developed and further improvements to simulate masticatory motion for observing chewing trajectory and its physiological constraints [16]. These models include measuring chewing force and jaw movement related to the physical properties of food [17], simulating bolus formation using a cylindrical chamber driven by a flat mechanical plunger [18], and assessing food texture using a robotic simulator [19]. In these models, focused on reproducing the chewing action and trajectory, it is still difficult to explain the volatile compounds released from different foods during mastication.…”
Section: Introductionmentioning
confidence: 99%