Evidence map›Paper›PMID 40807858›Full record

ArticleSensors (Basel, Switzerland)2025

New Imaging Method of Mobile Phone-Based Colorimetric Sensor for Iron Quantification.

Ngan Anh Nguyen, Asher Hendricks, Emily Montoya, Amber Mayers, Diwitha Rajmohan, Aoife Morrin, Margaret McCaul, Nicholas Dunne, Noel O'Connor, Andreas Spanias and 2 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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. 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

12 authors.

Ngan Anh NguyenSchool of Engineering for Matter, Transport and Energy, Arizona State University, Tempe, AZ 85281, USA.
Asher HendricksSchool of Engineering for Matter, Transport and Energy, Arizona State University, Tempe, AZ 85281, USA.
Emily MontoyaSchool of Engineering for Matter, Transport and Energy, Arizona State University, Tempe, AZ 85281, USA.
Amber MayersSchool of Engineering for Matter, Transport and Energy, Arizona State University, Tempe, AZ 85281, USA.
Diwitha RajmohanSchool of Engineering for Matter, Transport and Energy, Arizona State University, Tempe, AZ 85281, USA.
Aoife MorrinSchool of Chemical Sciences, Dublin City University, D09 V209 Dublin, Ireland.ORCID 0000-0002-3031-4794
Margaret McCaulSchool of Chemical Sciences, Dublin City University, D09 V209 Dublin, Ireland.
Nicholas DunneAdvanced Manufacturing Research Centre (I-Form), School of Mechanical and Manufacturing Engineering, Dublin City University, D09 NA55 Dublin, Ireland.ORCID 0000-0003-4649-2410
Noel O'ConnorSchool of Electronic Engineering, Dublin City University, D09 V209 Dublin, Ireland.
Andreas SpaniasSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA.
Gregory RauppSchool of Engineering for Matter, Transport and Energy, Arizona State University, Tempe, AZ 85281, USA.
Erica ForzaniSchool of Engineering for Matter, Transport and Energy, Arizona State University, Tempe, AZ 85281, USA.

Funding

National Science Foundation 2107439
6 · The paper itself

Abstract

Blood iron levels are related to many health conditions, affecting hundreds of millions of individuals worldwide. To aid in the prevention and treatment of iron-related disorders, previous research has developed a low-cost, accurate, point-of-care method for measuring iron from a single finger-prick blood sample. This study builds upon that work by introducing an improved imaging method that accurately reads sensor images irrespective of variations in environmental illumination and camera quality. Smartphone cameras were used as analytical tools, demonstrating an average coefficient of variation of 5.13% across different phone models, and absorbance results were found to be improved by 8.80% compared to the method in a previous study. The proposed method successfully enhances iron detection accuracy under diverse lighting conditions, paving the way for smartphone-based sensing of other colorimetric reactions involving various analytes.

Indexed as

Cell PhoneColorimetryIronHumansPoint-of-Care SystemsSmartphoneIronbiosensorschemical sensorsimage color analysisiron detectionpoint-of-care sensorsmartphone-based detectionvertical flow assay

Identifiers

PMID40807858
PMCPMC12349305

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.