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人工智能驱动的多模式大脑状态解码用于个性化的闭环TENS:全面审查

Jiahao Du1, Shengli Luo1, Ping Shi1

  • 1Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China.

Brain sciences
|September 27, 2025
PubMed
概括
此摘要是机器生成的。

通过皮肤电神经刺激 (TENS) 可以成为使用大脑状态解码的个性化疗法. 这种适应性方法超越了动态慢性疼痛条件的静态治疗.

关键词:
大脑状态解码的解码闭环神经调制是关闭循环的神经调制.多模式神经成像技术多模式神经成像技术个性化的神经调节通过皮肤进行电神经刺激 (TENS).

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科学领域:

  • 神经科学是一个神经科学.
  • 生物医学工程 生物医学工程
  • 人工智能的人工智能

背景情况:

  • 慢性疼痛是一种复杂的大脑全方位的疾病,目前的静态治疗方法无法充分管理.
  • 穿皮电神经刺激 (TENS) 是一种需要推进的传统模式.
  • 精确的神经调制需要个性化,适应性的方法.

研究的目的:

  • 将TENS转变为一个智能,适应性治疗平台的框架概述.
  • 探索神经成像和机器学习的整合,以实现个性化的TENS.
  • 从固定的TENS协议转向闭环,响应性神经调节.

主要方法:

  • 整合多式神经成像 (fMRI,EEG,fNIRS) 与实时机器学习.
  • 利用TENS的大脑状态解码和自适应算法.
  • 开发一个翻译框架来重新设计TENS技术.

主要成果:

  • 设想TENS从开环调制到闭环调制的范式转变.
  • 强调人工智能驱动的基础设施在神经调制中的潜力.
  • 确定关键的神经生理机制和伦理考虑.

结论:

  • TENS可以发展成为一个精确的神经调节系统,适合个体慢性疼痛特征.
  • 这种适应性方法承诺更有效地管理慢性疼痛.
  • 该框架支持超越疼痛管理的更广泛的神经适应医疗保健应用.