Materials and System Design for Self-Decision Bioelectronic Systems

  • Qiankun Zeng
  • , Hong Liu
  • , Yongheng Zhang
  • , Youbin Zheng
  • , Xuyin Ding
  • , Mengni Zhu
  • , Guoyue Shi
  • , Yan Wang
  • , Hossam Haick*
  • , Min Zhang*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Self-decision bioelectronic systems mark a transformative leap from conventional ‘sense-then-treat’ paradigms toward autonomous, closed-loop therapeutics, with material innovation serving as the pivotal enabler. This review posits that material innovation is the pivotal enabler of this transition, seamlessly integrating high-performance sensing, intelligent computation, and adaptive intervention. We elucidate how recent advances in electrochemical, electrophysiological, optical, and mechanical sensors fabricated from soft conductors, responsive polymers, and nanocomposites yield critical data streams for reliable physiological monitoring. We further explore how decision-making architectures, ranging from threshold-based logic to neuromorphic computation, transform these data into real-time therapeutic commands. Diverse material platforms are positioned as the central drivers of functional outputs, enabling precise electrical stimulation, on-demand drug delivery, mechanical actuation, and optical modulation, as demonstrated in artificial pancreas systems, neurointerventions, and smart wound dressings. Finally, we discuss system-level integration strategies and confront the enduring challenges, including biointegration, sustainable power, and regulatory translation, that must be overcome for clinical adoption. By threading the narrative through the lens of material innovation, this review not only surveys the current landscape but also provides a unique materials- and engineering-oriented perspective, aiming to chart a roadmap for next-generation autonomous and personalized medicine.

Original languageEnglish
JournalAdvanced Materials
DOIs
StateAccepted/In press - 2026

Keywords

  • biosensors
  • closed-loop systems
  • functional materials
  • neuromorphic computation
  • personalized medicine
  • self-decision bioelectronics

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