Non-enzymatic sweat sensors for pediatric continuous glucose monitoring: a systematic review of engineering readiness and the cost-accuracy trade-off

Continuous glucose monitoring (CGM) in children with type 1 diabetes is faced with major challenges due to prohibitive price, invasiveness and lack of compliance with insulin of the currently available interstitial devices, which is particularly severe in low- and middle-income countries (LMICs). To investigate emerging solutions, we have undertaken a systematic review (2016–2025) of non-invasive, sweat-based glucose sensors and used a structured biomedical engineering model to determine the technological maturity and pediatric and global health usage of the sensors. The review of 25 peer-reviewed articles indicates a significant shift to non-enzymatic sensing schemes based on strong approaches and incorporating highly sensitive nanomaterials like MXene and scalable libraries of fabrications. An analysis of qualitative cost accuracy trade-off, formalized by new, specially developed LMIC Scalability Score, proves that whereas complex and expensive systems would reach the lowest mean absolute relative difference (MARD), simpler and highly scalable devices would reach the same performance with a MARD value under 10.5%, making them possible and low-cost variants. To this end, the essential interventions that can be done to facilitate clinical translation in the short term are the design of advanced physiological time-lag simulations and the implementation of strong, age-focused pediatric clinical trials to bridge the technology innovation and clinical practice gap.

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Publication Details

Journal
BMC Biomedical Engineering
Published
2026-04-15
DOI
https://doi.org/10.1186/s42490-026-00109-8
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
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article

Non-enzymatic sweat sensors for pediatric continuous glucose monitoring: a systematic review of engineering readiness and the cost-accuracy trade-off

Deborah DARAMOLA, Olumhense Benedict Adoghe, Emmanuel Dominic Ephraim, Emmanuel Francis Kibuebu et al.
BMC Biomedical Engineering
Advanced Sensor and Energy Harvesting Materials
article

Non-enzymatic sweat sensors for pediatric continuous glucose monitoring: a systematic review of engineering readiness and the cost-accuracy trade-off

Deborah DARAMOLA, Olumhense Benedict Adoghe, Emmanuel Dominic Ephraim, Emmanuel Francis Kibuebu, Oluwanifemi Temiloluwa Bolaji
article en

Abstract

Continuous glucose monitoring (CGM) in children with type 1 diabetes is faced with major challenges due to prohibitive price, invasiveness and lack of compliance with insulin of the currently available interstitial devices, which is particularly severe in low- and middle-income countries (LMICs). To investigate emerging solutions, we have undertaken a systematic review (2016–2025) of non-invasive, sweat-based glucose sensors and used a structured biomedical engineering model to determine the technological maturity and pediatric and global health usage of the sensors. The review of 25 peer-reviewed articles indicates a significant shift to non-enzymatic sensing schemes based on strong approaches and incorporating highly sensitive nanomaterials like MXene and scalable libraries of fabrications. An analysis of qualitative cost accuracy trade-off, formalized by new, specially developed LMIC Scalability Score, proves that whereas complex and expensive systems would reach the lowest mean absolute relative difference (MARD), simpler and highly scalable devices would reach the same performance with a MARD value under 10.5%, making them possible and low-cost variants. To this end, the essential interventions that can be done to facilitate clinical translation in the short term are the design of advanced physiological time-lag simulations and the implementation of strong, age-focused pediatric clinical trials to bridge the technology innovation and clinical practice gap.

BMC Biomedical EngineeringVol. 8(1)
Bells University of Technology (NG), Achievers University (NG)
Openalex Percentile: Top 30%
Advanced Sensor and Energy Harvesting Materials
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