Authors
Xinyi Wang, Yuying Lin, Rubing Xiong, Jing Liu, Yue Liu, Zijie Li, Yongmei Chen, Yong Xia, Zhiqi Li, Lei Mou, Meiling Liu
Published in
Analytica chimica acta. Volume 1421. Pages 346006. Nov 01, 2026. Epub Jul 23, 2026.
Abstract
Continuous lactate monitoring provides valuable information on metabolic dynamics during exercise and recovery. Enzymatic lactate sensors commonly use lactate oxidase, whose catalytic response depends on local oxygen availability. As physiological oxygen levels fluctuate, a calibration model established under one oxygen condition may generate substantial measurement bias under another condition. Existing wearable lactate sensors generally use a single calibration model and therefore cannot compensate for oxygen-dependent changes in sensor response. The key problem addressed in this study is the lack of an oxygen-adaptive calibration strategy for accurate continuous lactate monitoring in complex physiological microenvironments.
We developed a wearable electrochemical platform based on a carbon nanotube/Prussian blue/lactate oxidase interface and integrated it with a custom portable microcircuit. The system classified currents less negative than -0.8 μA as hypoxic and those more negative than -0.8 μA as aerobic, and applied the corresponding calibration model in real time. The sensor showed linear responses from 2 to 12 mM lactate, with sensitivities of 0.2247 μA/mM under aerobic conditions and 0.01256 μA/mM under hypoxic conditions. Plasma measurements agreed closely with a commercial biochemical analyzer (r = 0.9860). In rats, sensor readings correlated strongly with blood lactate assay results during both aerobic (r = 0.9766) and hypoxic (r = 0.9316) phases. The oxygen-adaptive strategy achieved a mean absolute relative difference of 4.86%, compared with 59.72% and 1028% for the single aerobic and hypoxic calibration models, respectively.
This study introduces an oxygen-adaptive calibration strategy that converts oxygen-dependent signal variation from a source of error into a basis for real-time model selection. By combining oxygen-condition classification with condition-matched calibration, the platform markedly improves lactate measurement accuracy across aerobic and hypoxic conditions. This approach provides a practical framework for continuous biosensing in physiologically variable microenvironments.
PMID:
42702438
Bibliographic data and abstract were imported from PubMed on 07 Sep 2026.
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