Evidence map›Paper›PMID 38441499›Full record

ArticleChemistryOpen2024

Wearable Electrochemical Sensor for Sweat-Based Potassium Ion and Glucose Detection in Exercise Health Monitoring.

Lei Ma, Wenhao Hou, Zhi Ji, Ziheng Sun, Muxi Li, Bolin Lian

Open access · goldAbstract read
In one paragraph

Article in ChemistryOpen, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.6field-weighted citation impact, top 11% of its field
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

5 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Review
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  4. Review
  5. 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

6 authors at 1 institution in 1 country.

Lei MaDepartment School of Information Science and Technology, Nantong University 9#, Seyuan road, Chongchuan district, Nantong, China.
Wenhao HouDepartment School of Information Science and Technology, Nantong University 9#, Seyuan road, Chongchuan district, Nantong, China.
Zhi JiDepartment School of Information Science and Technology, Nantong University 9#, Seyuan road, Chongchuan district, Nantong, China.
Ziheng SunDepartment School of Information Science and Technology, Nantong University 9#, Seyuan road, Chongchuan district, Nantong, China.
Muxi LiDepartment School of Information Science and Technology, Nantong University 9#, Seyuan road, Chongchuan district, Nantong, China.
Bolin LianDepartment School of Life science, Nantong University 9#, Seyuan road, Chongchuan district, Nantong, China.ORCID 0000-0002-3537-2213
Nantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing prevalence of wearable devices has sparked a growing interest in real-time health monitoring and physiological parameter tracking. This study focuses on the development of a cost-effective sweat analysis device, utilizing microfluidic technology and selective electrochemical electrodes for non-invasive monitoring of glucose and potassium ions. The device, through real-time monitoring of glucose and potassium ion levels in sweat during physical activity, issues a warning signal when reaching experimentally set thresholds (K+ concentration at 7.5 mM, glucose concentrations at 60 μM and 120 μM). This alerts users to potential dehydration and hypoglycemic conditions. Through the integration of microfluidic devices and precise electrochemical analysis techniques, the device enables accurate and real-time monitoring of glucose and potassium ions in sweat. This advancement in wearable technology holds significant potential for personalized health management and preventive care, promoting overall well-being, and optimizing performance during physical activities.

Indexed as

Electrochemical TechniquesExerciseGlucosePotassiumSweatWearable Electronic DevicesBiosensing TechniquesHumansMonitoring, PhysiologicGlucosePotassiumElectrochemistryMicrofluidic technologySensorsSweat analysisWearable devices

Identifiers

PMID38441499
PMCPMC11319218
OpenAlexW4392456616

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.