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An Implantable System Design Based on Neuromorphic Memristor for Post-Craniotomy Intracranial Pressure Monitoring

  • Teng Wu
  • , Kun Wang
  • , Bai Sun
  • , Zelin Cao
  • , Junxiang Gu
  • , Meirou Liang
  • , Yifan Le
  • , Fan Li
  • , Jian Wang
  • , Yifan Xiao
  • , Mengna Wang
  • , Longhui Fu
  • , Kaikai Gao
  • , Haoyuan Wang
  • , Hui Ma
  • , Xincheng Du
  • , Jiajun Liu
  • , Jianqiang Qu
  • , Chang Liu
  • , Guangdong Zhou
  • Jinyou Shao, Xianxia Yan
  • The Second Affiliated Hospital of Xi'an Jiaotong University
  • Xi'an Jiaotong University
  • Air Force Medical University
  • Xijing Hospital
  • Shaanxi University of Chinese Medicine
  • Xidian University
  • Tangdu Hospital, Fourth Military Medical University
  • Northwest University China
  • Southwest University

科研成果: 期刊稿件文章同行评审

3 引用 (Scopus)

摘要

Craniotomy, a complex neurosurgical intervention, carries significant risks of postoperative complications including intracerebral hemorrhage (ICH) and cerebral edema, causing elevated intracranial pressure (ICP) and life-threatening cerebral herniation. However, the current ventricular catheter ICP monitoring technologies pose risks of infection and hemorrhage, and restrict patient mobility during medical procedures. There is thus an urgent need to develop ICP monitoring technologies that simultaneously achieve sensitivity, safety, and portability. Memristors, with their integrated memory, sensing, and neuromorphic computing capabilities, offer a promising solution to traditional monitoring bottlenecks. In this work, we innovatively developed an Ag/WO3/MnO2/FTO-structured memristor and validated its pressure signal encoding capability in vitro via integration with a pressure sensor. A collagenase-induced ICH animal model was established to simulate postcraniotomy intracranial hypertension. Following model induction, the sensor-memristor system was implanted for intracranial pressure signal acquisition and encoding. The encoded signals were prospectively processed through a memristor-based logic circuit for noise reduction, and analyzed and classified via a memristive neural network. This study demonstrates the potential of implantable memristor-sensor system for postcraniotomy ICP monitoring and underscores its role in enhancing neurosurgical care, which also provides innovative insights for designing efficient, real-time, and low-power consumption implantable pressure monitoring devices for medical health monitoring.

源语言英语
页(从-至)57284-57296
页数13
期刊ACS Applied Materials and Interfaces
17
41
DOI
出版状态已出版 - 15 10月 2025

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