Evidence map›Paper›PMID 41228776›Full record

ReviewSensors (Basel, Switzerland)2025

A Review of Graphene-Integrated Biosensors for Non-Invasive Biochemical Monitoring in Health Applications.

Sourabhi Debnath, Tanmoy Debnath, Manoranjan Paul

Abstract readReview
In one paragraph

Review 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
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

3 authors.

Sourabhi DebnathSchool of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.ORCID 0009-0007-2560-6999
Tanmoy DebnathSchool of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.ORCID 0000-0002-3530-5926
Manoranjan PaulSchool of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.ORCID 0000-0001-6870-5056

Funding

Artificial Intelligence and Cyber Futures Institute, Charles Sturt University, Australia N/A
6 · The paper itself

Abstract

This review explores the transformative potential of graphene-based, non-invasive biochemical sensors in the context of real-time health monitoring and personalised medicine. Traditional diagnostic methods often involve invasive procedures that can be uncomfortable, pose risks, and limit the frequency of monitoring. In contrast, wearable sensors incorporating graphene offer a compelling alternative by enabling continuous, real-time tracking of physiological and biochemical signals with minimal intrusion. Graphene's exceptional electrical conductivity, mechanical flexibility, biocompatibility, and high surface-area-to-volume ratio make it ideally suited for integration into skin-conformal sensor platforms. These properties not only enhance sensitivity and signal fidelity but also promote user comfort and long-term wearability, critical factors for the adoption of wearable health technologies. The discussion evaluates current developments in the design and deployment of graphene-based biosensors, with particular attention given to their role in managing chronic conditions, supporting preventative healthcare, and facilitating decentralised diagnostics. By bridging materials science and biomedical engineering, this review positions graphene as a key enabler in the shift towards more proactive, patient-centred healthcare models. The text also identifies ongoing challenges and future directions in sensor design, aiming to inform researchers working at the intersection of advanced materials and medical technology.

Indexed as

Biosensing TechniquesGraphiteElectric ConductivityHumansMonitoring, PhysiologicWearable Electronic DevicesGraphitebiochemical sensorsbiomedical applicationscancer detectiondisease detectiondrug detectionglucose detectiongraphenehealth monitoringnon-invasive sensorstumour detection

Identifiers

PMID41228776
PMCPMC12608150

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.