Evidence map›Paper›PMID 40578860›Full record

ArticleBMJ open2025

Wearable sensing in eating episode monitoring: an updated systematic review protocol.

Jiaying Zhou, Mingzhu Cai, Mayue Shi

Abstract read
In one paragraph

Article in BMJ open, 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. Review
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

3 authors.

Jiaying ZhouDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.ORCID http://orcid.org/0009-0009-4937-1834
Mingzhu Cai *Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK m.shi16@imperial.ac.uk m.cai18@imperial.ac.uk.ORCID http://orcid.org/0000-0002-1474-0224
Mayue Shi *Department of Electrical and Electronic Engineering, Imperial College London, London, UK m.shi16@imperial.ac.uk m.cai18@imperial.ac.uk.ORCID http://orcid.org/0000-0001-8539-6873

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionObjective and accurate dietary monitoring is critical for comprehensive dietary assessment and improving nutritional health outcomes. The rapid advancement of wearable sensing technology presents a promising solution for effective dietary monitoring by reducing recall bias and enhancing user convenience, with potential benefits for both clinical chronic disease management and nutritional research. This systematic review aims to evaluate the effectiveness and feasibility of wearable sensors in monitoring dietary behaviours, while also examining the latest advancements in the field since 2020. METHODS AND ANALYSIS: This protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols guidelines for systematic review reporting. We will conduct a comprehensive search across MEDLINE, EMBASE, PubMed, IEEE Xplore and Web of Science to identify studies published between January 2020 and March 2025 involving human participants using wearable sensors for dietary intake monitoring. Studies that focus solely on the development of algorithms or applications for these sensors will be excluded. The outcomes of this review will include evaluations of sensor design, performance metrics and user experience. ETHICS AND DISSEMINATION: Findings of this systematic review will be disseminated through peer-reviewed journals, conferences and seminar presentations. The data used do not include individual patient data, so no ethical approval is required.

Indexed as

Feeding BehaviorWearable Electronic DevicesHumansResearch DesignSystematic Reviews as TopicDietary behaviourfood intakewearable sensor

Identifiers

PMID40578860
PMCPMC12207139

What OpenQuestion holds

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LicenceCC BY-NC
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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.