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Related Experiment Video

Updated: Jun 4, 2026

Fabrication and Characterization of a Conformal Skin-like Electronic System for Quantitative, Cutaneous Wound Management
08:50

Fabrication and Characterization of a Conformal Skin-like Electronic System for Quantitative, Cutaneous Wound Management

Published on: September 2, 2015

Artificial Intelligence-Driven Janus Dressing for Visual Wound Theranostics.

Zhengjie Chen1, Yiming Zhu1, Hongyang Lou1

  • 1Strait Institute of Flexible Electronics (SIFE, Future Technologies), Fujian Key Laboratory of Flexible Electronics, Fujian Normal University, Fuzhou 350117, China.

ACS Nano
|June 2, 2026
PubMed
Summary

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This summary is machine-generated.

This study introduces a smart wound dressing that monitors pH to predict infection and healing. The AI-powered platform extracts wound fluid for real-time analysis, improving wound care.

Area of Science:

  • Biomaterials Science
  • Wound Healing Research
  • Digital Health Technologies

Background:

  • Wound exudate pH is a critical indicator of infection and healing.
  • Current real-time pH monitoring is hindered by challenges in exudate extraction and sensor stability.
  • Existing pH indicators often suffer from instability and leaching issues.

Purpose of the Study:

  • To develop an integrated theranostic wound dressing for real-time pH monitoring and antibacterial therapy.
  • To enable accurate, in situ assessment of wound infection risk and healing status.
  • To create a closed-loop system for precision wound management using AI and digital health tools.

Main Methods:

  • Fabrication of an asymmetric Janus wound dressing with unidirectional exudate transport.
Keywords:
Janus dressingantibacterialartificial intelligenceinfected woundtheranosticswound monitoring

Related Experiment Videos

Last Updated: Jun 4, 2026

Fabrication and Characterization of a Conformal Skin-like Electronic System for Quantitative, Cutaneous Wound Management
08:50

Fabrication and Characterization of a Conformal Skin-like Electronic System for Quantitative, Cutaneous Wound Management

Published on: September 2, 2015

  • Integration of curcumin/Ag nanoparticles for antibacterial properties.
  • Development of a stable, leaching-resistant colorimetric pH sensor using phenol red encapsulated in zeolitic imidazolate framework-8 nanoparticles.
  • Utilization of a deep-learning-assisted smartphone application for lighting-independent pH quantification.

    • Main Results:

    • The developed dressing effectively drains exudate and provides a broad dynamic color range for pH sensing.
    • The encapsulated phenol red sensor demonstrated enhanced sensitivity and resistance to leaching.
    • In vitro and in vivo studies confirmed infection suppression, accelerated wound closure, and relevant biochemical feedback.
    • The AI-assisted platform enabled objective in situ assessment of wound conditions.

    Conclusions:

    • The proposed theranostic wound dressing offers a comprehensive solution for precision wound management.
    • This AI-assisted approach integrates wound microenvironment engineering with digital health tools for improved patient outcomes.
    • The platform demonstrates significant potential for clinical translation in monitoring and treating chronic wounds.