Evidence map›Paper›PMID 40796652›Full record

ArticleJournal of exposure science & environmental epidemiology2026

Application of a computer vision algorithm to quantify the frequency and duration of children's microactivities in different play scenarios.

Sara N Lupolt, Qinfan Lyu, Guofeng Zhang, Jiahao Wang, Stacey Tang, Jamie Cho, Christina Huynh, Alan Yuille, Kristin Voegtline, Keeve E Nachman

Abstract read
In one paragraph

Article in Journal of exposure science & environmental epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Sara N LupoltDepartment of Environmental Health & Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. slupolt1@jhu.edu.ORCID http://orcid.org/0000-0001-6263-5333
Qinfan LyuDepartment of Environmental Health & Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Guofeng ZhangDepartment of Computer Science, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA.
Jiahao WangDepartment of Computer Science, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA.
Stacey TangDepartment of Pediatrics, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Jamie ChoDepartment of Neuroscience, Johns Hopkins Krieger School of Arts and Sciences, Baltimore, MD, USA.
Christina HuynhDepartment of Environmental Health & Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Alan YuilleDepartment of Computer Science, Johns Hopkins Whiting School of Engineering, Baltimore, MD, USA.
Kristin VoegtlineDepartment of Pediatrics, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Keeve E NachmanDepartment of Environmental Health & Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. knachman@jhu.edu.ORCID http://orcid.org/0000-0003-4925-4151

Funding

Pilot Project ProgramP30ES032756 · NIEHS · JOHNS HOPKINS UNIVERSITY · PI Marsha Wills-Karp · 2022 to 2026
$6.0M
NIEHS NIH HHS P30 ES032756
6 · The paper itself

Abstract

backgroundMicroactivity rates, including hand- and object-to-mouth contacts, are inputs for modeling children's exposure to chemicals in soil and dust and from toys. EPA's confidence in its current recommended microactivity frequency estimates for use in exposure assessments is low.

objectiveWe aimed to quantify children's hand- and object-to-mouth microactivities using a novel computer vision method and explored differences by lifestage and fine and gross motor development.

methodsWe recorded 20-minute videos of 61 children aged 6 to ≤18 months playing in their homes under two play contexts. We employed a novel computer vision approach that uses multiview video to estimate 3D body keypoints and measure hand-to-mouth distances, enabling quantification of each child's hand-and object-to-mouth contact without the need for human coders. We explored differences in the frequency and duration of microactivity contacts by age and motor development.

resultsWe observed at least one instance of a microactivity event (i.e., hand- or object-to-mouth contact) among 41 of the 61 participants observed. The median rate of object-to-mouth contacts (23 contacts/hour) was greater than hand-to-mouth contacts (6 contacts/hour). We did not observe significant differences in the frequency of either hand-to-mouth and object-to-mouth contacts by age or motor development, but we did observe greater variation in object-to-mouth contacts than previously reported. The median durations of hand- and object-to-mouth contact were 0.24 min/hour and 1.57 min/hour, respectively. SIGNIFICANCE: Our observed rates of microactivities are comparable and in some cases, less than the current EPA central tendency estimates recommended for use in risk assessments. Our high-end (95th percentile) estimate for object-to-mouth contacts, however, underscores the need for better characterization of population variability in order to protect the most highly exposed children. IMPACT: We apply a novel computer vision algorithm to quantify the microactivity frequencies and durations of 61 children 6 to ≤18 months old. We examine differences in these frequencies and durations by child lifestage and motor development. Demonstration of this method paves the way for future, larger studies that observe children for longer durations to develop confident estimates of population variability in microactivity behaviors. These and future data could inform analyses in support of the revision of EPA recommendations for children's soil and dust ingestion rates.

Indexed as

AlgorithmsEnvironmental ExposurePlay and PlaythingsChild DevelopmentFemaleHumansInfantMaleVideo RecordingDustHand-to-mouthMicroactivityObject-to-mouthSoilVideography

Identifiers

PMID40796652
PMCPMC13085206

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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.