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A Fully-Printed Wearable Bandage-Based Electrochemical Sensor with pH Correction for Wound Infection Monitoring. | LitMetric

AI Article Synopsis

  • Wearable sensing systems are being developed to monitor health by analyzing biofluids, yet wound diagnosis is still difficult due to limitations in current sensors for measuring pH and related substances.
  • This article presents a new flexible sensor array that can detect pyocyanin while adjusting for pH changes, enhancing the accuracy of wound monitoring.
  • Custom screen-printable inks and advanced data analysis methods have been employed to create sensitive sensors that could lead to affordable and user-friendly wearable devices for personalized health monitoring.

Article Abstract

Wearable sensing systems have been designed to monitor health conditions in real-time by detecting analytes in human biofluids. Wound diagnosis remains challenging, necessitating suitable materials for high-performance wearable sensors to offer prompt feedback. Existing devices have limitations in measuring pH and the concentration of pH-dependent electroactive species simultaneously, which is crucial for obtaining a comprehensive understanding of wound status and optimizing biosensors. Therefore, improving materials and analysis system accuracy is essential. This article introduces the first example of a flexible array capable of detecting pyocyanin, a bacterial virulence factor, while correcting dynamic pH fluctuations. We demonstrate that this combined sensor enhances accuracy by mitigating the impact of pH variability on pyocyanin sensor response. Customized screen-printable inks were developed to enhance analytical performance. The analytical performances of two sensitive sensor systems (i.e., fully-printed porous graphene/multiwalled carbon nanotube (CNT) and polyaniline/CNT composites for pyocyanin and pH sensors) are evaluated. Partial least square regression is employed to analyze nonzero-order data arrays from square wave voltammetric and potentiometric measurements of pyocyanin and pH sensors to establish a predictive model for pyocyanin concentration in complex fluids. This sensitive and effective strategy shows potential for personalized applications due to its affordability, ease of use, and ability to adjust for dynamic pH changes.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11599554PMC
http://dx.doi.org/10.1007/s40820-024-01561-8DOI Listing

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