Prediction of Glucose Sensor Sensitivity in the Presence of Biofouling Using Machine Learning and Electrochemical Impedance Spectroscopy

Sharma, Hrishita; Kalita, Deepjyoti; Naskar, Ujjal; Mishra, Braja Gopal; Kumar, Prasoon; Mirza, Khalid B.

doi:10.1109/jsen.2023.3289619

Cited by 5 publications

(2 citation statements)

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“…This is because these sensors are constructed using materials that are prone to passivation by fouling agents (i.e., proteins, amino acids, lipids, etc.) that form an impermeable layer on the electrode surface, affecting charge transfer kinetics between the target analyte and the electrode surface [15]. This effect discourages the application of biosensors for continuous monitoring since fouling degrades the sensor surface, resulting in a low signal-to-noise ratio and reduced sensitivity [12,15].…”

Section: Introductionmentioning

confidence: 99%

“…that form an impermeable layer on the electrode surface, affecting charge transfer kinetics between the target analyte and the electrode surface [15]. This effect discourages the application of biosensors for continuous monitoring since fouling degrades the sensor surface, resulting in a low signal-to-noise ratio and reduced sensitivity [12,15]. Therefore, it is critical to develop methods to address biofouling-related problems to continuously monitor metabolites, such as glucose, in real time over extended periods.…”

Section: Introductionmentioning

confidence: 99%

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Redox-Modified Nanostructured Electrochemical Surfaces for Continuous Glucose Monitoring in Complex Biological Fluids

Janfaza,

Radha Shanmugam,

Jolly

et al. 2024

Nanomaterials

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Continuous glucose monitoring is valuable for people with diabetes but faces limitations due to enzyme–electrode interactions and biofouling from biological samples that reduce sensor sensitivity and the monitoring performance. We created an enzyme-based electrochemical system with a unique nanocomposite coating that incorporates the redox molecule, aminoferrocene (NH2-Fc). This coating enhances stability via electroactivity and reduces nonspecific binding, as demonstrated through cyclic voltammetry. Our approach enables real-time glucose detection via chronoamperometry with a calculated linear range of 0.5 to 20 mM and a 1 mM detection limit. Validated with plasma and saliva, this platform shows promise for robust metabolite detection in clinical and research contexts. This versatile platform can be applied to accurately monitor a wide range of metabolites in various biological matrices, improving patient outcomes.

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Section: Introductionmentioning

confidence: 99%