Next Article in Journal
A Resilient Distributed Pareto-Based PSO for Edge-UAVs Deployment Optimization in Internet of Flying Things
Previous Article in Journal
Assessment of Neutron Radiation Effects on the Fiber Optics Current Sensor Performance During JET DTE2 Experimental Campaign
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Review

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

1
School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia
2
Artificial Intelligence and Cyber Futures Institute, Charles Sturt University, Bathurst, NSW 2795, Australia
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(21), 6553; https://doi.org/10.3390/s25216553 (registering DOI)
Submission received: 6 August 2025 / Revised: 10 October 2025 / Accepted: 18 October 2025 / Published: 24 October 2025
(This article belongs to the Section Biomedical Sensors)

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.
Keywords: graphene; non-invasive sensors; biochemical sensors; biomedical applications; health monitoring; disease detection; cancer detection; tumour detection; glucose detection; drug detection graphene; non-invasive sensors; biochemical sensors; biomedical applications; health monitoring; disease detection; cancer detection; tumour detection; glucose detection; drug detection

Share and Cite

MDPI and ACS Style

Debnath, S.; Debnath, T.; Paul, M. A Review of Graphene-Integrated Biosensors for Non-Invasive Biochemical Monitoring in Health Applications. Sensors 2025, 25, 6553. https://doi.org/10.3390/s25216553

AMA Style

Debnath S, Debnath T, Paul M. A Review of Graphene-Integrated Biosensors for Non-Invasive Biochemical Monitoring in Health Applications. Sensors. 2025; 25(21):6553. https://doi.org/10.3390/s25216553

Chicago/Turabian Style

Debnath, Sourabhi, Tanmoy Debnath, and Manoranjan Paul. 2025. "A Review of Graphene-Integrated Biosensors for Non-Invasive Biochemical Monitoring in Health Applications" Sensors 25, no. 21: 6553. https://doi.org/10.3390/s25216553

APA Style

Debnath, S., Debnath, T., & Paul, M. (2025). A Review of Graphene-Integrated Biosensors for Non-Invasive Biochemical Monitoring in Health Applications. Sensors, 25(21), 6553. https://doi.org/10.3390/s25216553

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop