Evidence map›Paper›PMID 41170363›Full record

ArticleFrontiers in nutrition2025

EateryTag: investigating unobtrusive edible tags using digital food fabrication.

Yamato Miyatake, Parinya Punpongsanon

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yamato MiyatakeGraduate School of Science and Engineering, Saitama University, Saitama, Japan.
Parinya PunpongsanonGraduate School of Science and Engineering, Saitama University, Saitama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-Food Interaction (HFI) examines how digital integration can enhance dining experiences, with food tagging playing a crucial role in connecting physical dining environments with digital information. Attaching optical tags to the surface or sides of food often detracts from its aesthetics, negatively impacting the perceived taste and overall dining experience. To address this issue, we propose an unobtrusive food tagging approach that embeds tags inside the food, maintaining both its visual appeal and sensory qualities. We first developed a tagging method using a 3D printer and proposed an end-to-end pipeline for embedding and retrieving the tags. We evaluated this method in terms of tag detectability, concealability, and the eating experience. Additionally, we developed tagging methods using molding and stamping to extend acceptability to the traditional cooking environment. Through a workshop with three home chefs, we found that these methods are accessible and easy to adopt for novice users. Our findings demonstrate the potential of embedded food tagging to integrate digital information into the dining experience without compromising culinary integrity. This approach offers new directions for HFI research and practical applications.

Indexed as

3D food printingcomputer visiondigital gastronomyedible taghuman-food interactionunobtrusive tagging

Identifiers

PMID41170363
PMCPMC12568387

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.