Evidence map›Paper›PMID 39598964›Full record

ArticleSensors (Basel, Switzerland)2024

Estimation of the Number of Active Sweat Glands Through Discrete Sweat Sensing.

Jelte R Haakma, Elisabetta Peri, Simona Turco, Eduard Pelssers, Jaap M J den Toonder, Massimo Mischi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Jelte R HaakmaDepartment of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.ORCID 0009-0001-5396-1935
Elisabetta PeriDepartment of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.ORCID 0000-0002-1231-9372
Simona TurcoDepartment of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.ORCID 0000-0002-1520-3930
Eduard PelssersMechanical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.
Jaap M J den ToonderMechanical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.ORCID 0000-0002-5923-4456
Massimo MischiDepartment of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.ORCID 0000-0002-1179-5385

Funding

Penta 19017
6 · The paper itself

Abstract

Sweat is a biomarker-rich fluid with potential for continuous patient monitoring via wearable devices. However, biomarker concentrations vary with the sweat rate per gland, posing a challenge for sweat sensing. To address this, we propose an algorithm to compute both the number of active sweat glands and their individual sweat rates. We developed models of sweat glands and a discrete sweat-sensing device to sense sweat volume. Our algorithm estimates the number of active glands by decomposing the signal into patterns generated by the individual sweat glands, allowing for the calculation of individual sweat rates. We assessed the algorithm's accuracy using synthetic datasets for varying physiological parameters (sweat rate and number of active sweat glands) and device layouts. The results show that device layout significantly affects accuracy, with error rates below 0.2% for low and medium sweat rates (below 0.2 nL min

Indexed as

AlgorithmsSweatSweat GlandsWearable Electronic DevicesBiomarkersBiosensing TechniquesHumansBiomarkersdiscrete sweat sensing devicehealth monitoringsweat

Identifiers

PMID39598964
PMCPMC11598459

What OpenQuestion 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 OpenQuestion graph.