Mastication Class Estimation for Food Bolus by Using Convolutional Neural Network

Nishi, Keiichiro; Shibata, Akinobu; Nagahama, Yuya; Kimura, Kou; Inoue, Masami; Higashimori, Mitsuru

doi:10.1109/smc.2019.8914079

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) 2019

DOI: 10.1109/smc.2019.8914079

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Mastication Class Estimation for Food Bolus by Using Convolutional Neural Network

Keiichiro Nishi

Akinobu Shibata

Yuya Nagahama³

et al.

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2024

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Enclosure area expansion and reduction mechanism for artificial mastication device

HASHIMOTO,

SHIBATA,

HASHIMOTO

et al. 2024

Transactions of the JSME (In Japanese)

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This paper discusses the design of the mechanism for an artificial mastication device that reproduces the formation of the food bolus by humans. A novel mechanism, the enclosure area expansion and reduction mechanism, that can gather fragments of food is proposed. In the proposed mechanism, multiple movable walls with common shape and sizes form a symmetrical enclosure area that contains the food fragments. Driven by a single actuator, all walls move coordinately so that the enclosure area reduces and expands for gathering the fragments. We first show the mathematical formulation of the geometrical conditions of the movable walls. We then design the movable walls and power transmission system for a prototype installed in the artificial mastication device. Finally, we present the experimental results, which validate the proposed method.

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Enclosure area expansion and reduction mechanism for artificial mastication device

HASHIMOTO,

SHIBATA,

HASHIMOTO

et al. 2024

Transactions of the JSME (In Japanese)

View full text Add to dashboard Cite

show abstract

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Mastication Class Estimation for Food Bolus by Using Convolutional Neural Network

Cited by 1 publication

References 15 publications

Enclosure area expansion and reduction mechanism for artificial mastication device

Enclosure area expansion and reduction mechanism for artificial mastication device

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