Next-generation smart wound dressings: AI integration, biosensors, and electrospun nanofibers for chronic wound therapy.

Journal: Journal of biomaterials science. Polymer edition
Published Date: Aug 6, 2025

Abstract

Polymeric biomaterials, particularly electrospun nanofibers, are increasingly central to the development of advanced wound dressings capable of supporting tissue regeneration while enabling real-time physiological monitoring. Chronic wounds associated with diabetes, vascular diseases, and cancer require continuous and personalized management, prompting the convergence of electrospun polymeric scaffolds with wearable biosensors and artificial intelligence (AI). These next-generation smart wound dressings utilize biocompatible polymer matrices functionalized with responsive sensing elements to monitor pH, temperature, moisture, oxygen saturation, and inflammatory biomarkers . Molecular-level interactions between polymeric components and biological tissues facilitate both therapeutic delivery and diagnostic functionality. AI, including deep and federated learning, enhances these systems by enabling data-driven prediction of healing trajectories and personalized interventions. Key advances in flexible electronics, self-powered systems, and closed-loop feedback mechanisms further enhance clinical applicability. However, challenges remain, including the biochemical stability of sensors in enzyme-rich environments, secure wireless communication, and the lack of standardized datasets and clinical validation frameworks. This review critically examines recent progress in AI-integrated polymeric wound care systems, emphasizing the design of functional polymeric scaffolds, biosensor-polymer interfaces, and future directions, including biosensor miniaturization, multi-omics data integration, and scalable cloud-based platforms. A collaborative roadmap is proposed to advance these intelligent biomaterial systems toward clinical translation in chronic wound care.

Authors

  • Naveen Palani
    Department of Physics and Nanotechnology, SRM Institute of Science and Technology, Chengalpattu District, Kattankulathur, Tamil Nadu 603203, India.
  • Keren Celestina Mendonce
    Department of Biotechnology, Faculty of Science and Humanities, SRM Institute of Science and Technology, Chengalpattu District, Kattankulathur, Tamil Nadu 603203, India.
  • Rabiya Riffath Syed Altaf
    Department of Physics and Nanotechnology, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Tamil Nadu, India.
  • Agilandeswari Mohan
    Centre for Research in Environment, Sustainability Advocacy and Climate Change (REACH), Directorate of Research, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Tamil Nadu, India.
  • Parthasarathy Surya
    Department of Research Analytics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India.
  • Monisha P
    PG & Research Department of Physics, Sri Sarada College for Women, Salem, Tamil Nadu, India.
  • K Radhakrishnan
    Department of Chemistry, Centre for Material Chemistry, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu 641021, India.
  • Vishnupriya Subramaniyan
    Department of Biotechnology, School of Bioengineering, SRM Institute of Science and Technology, Potheri, Kattankulathur, Chengalpattu District, Tamil Nadu, India.
  • Suriyaprakash Rajadesingu
    Centre for Research in Environment, Sustainability Advocacy and Climate Change (REACH), Directorate of Research, SRM Institute of Science and Technology, Chengalpattu District, Kattankulathur, Tamil Nadu 603203, India.

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