Evidence map›Paper›PMID 37747817›Full record

ReviewACS sensors2023

Recent Advances in Skin-Interfaced Wearable Sweat Sensors: Opportunities for Equitable Personalized Medicine and Global Health Diagnostics.

Kaylee M Clark, Tyler R Ray

Abstract readReview
In one paragraph

Review in ACS sensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
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  3. Sweat components as a promising monitoring tool for systemic diseases.The journal of physiological sciences : JPS · 2026
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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.

Kaylee M ClarkDepartment of Mechanical Engineering, University of Hawai'i at Ma̅noa, Honolulu, Hawaii 96822, United States.ORCID 0000-0002-3082-8314
Tyler R RayDepartment of Mechanical Engineering, University of Hawai'i at Ma̅noa, Honolulu, Hawaii 96822, United States.ORCID 0000-0001-7047-9676

Funding

TRPA1 Physiology in Diabetes, Metabolic Syndrome, and MetabolismP20GM113134 · NIGMS · UNIVERSITY OF HAWAII AT MANOA · PI Kathryn Jaques Schunke · 2017 to 2026
$21.5M
NIGMS NIH HHS P20 GM113134
6 · The paper itself

Abstract

Recent advances in skin-interfaced wearable sweat sensors enable the noninvasive, real-time monitoring of biochemical signals associated with health and wellness. These wearable platforms leverage microfluidic channels, biochemical sensors, and flexible electronics to enable the continuous analysis of sweat-based biomarkers such as electrolytes, metabolites, and hormones. As this field continues to mature, the potential of low-cost, continuous personalized health monitoring enabled by such wearable sensors holds significant promise for addressing some of the formidable obstacles to delivering comprehensive medical care in under-resourced settings. This Perspective highlights the transformative potential of wearable sweat sensing for providing equitable access to cutting-edge healthcare diagnostics, especially in remote or geographically isolated areas. It examines the current understanding of sweat composition as well as recent innovations in microfluidic device architectures and sensing strategies by showcasing emerging applications and opportunities for innovation. It concludes with a discussion on expanding the utility of wearable sweat sensors for clinically relevant health applications and opportunities for enabling equitable access to innovation to address existing health disparities.

Indexed as

SweatWearable Electronic DevicesGlobal HealthPrecision MedicineSkinbiosensorsepidermal microfluidicsnoninvasive health monitoringsweat analysiswearable sensors

Identifiers

PMID37747817
PMCPMC11211071

What OpenQuestion holds

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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.