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人工智能 (AI) 通过提高护理质量和精度来增强中风康复. 这份对704项研究的综述表明,人工智能应用从基本概念发展到用于运动功能,机器人辅助和预测建模的先进技术.

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科学领域:

  • 神经科学与康复医学 神经科学与康复医学

背景情况:

  • 在全球范围内,中风是导致成人残疾的主要原因.
  • 人工智能和传感器技术的进步有可能改善中风恢复和康复结果.
  • 在成人中风康复中对人工智能应用的现有研究需要全面的描述.

研究的目的:

  • 在成人中风恢复和康复中识别和分类人工智能应用.
  • 分析随着时间的推移,人工智能技术在这个领域的进展.
  • 总结来自大量相关研究的关键发现.

主要方法:

  • 从电子数据库中对同行评审文章进行范围审查,截至2024年1月.
  • 用人工智能增强的多方法,数据驱动的技术,包括主题和主题聚类,用于数据提取.
  • 分析了704项研究,以确定共同的主题和时间模式.

主要成果:

  • 出现了四个主要主题:损伤,辅助干预,预测和成像以及神经科学.
  • 人工智能应用从最初的概念发展到复杂的监督学习,人工神经网络 (ANN) 和自然语言处理 (NLP).
  • 专注于上肢康复,利用机器学习 (ML),深度学习和诸如惯性测量单位 (IMU) 等传感器进行运动分析.

结论:

  • 人工智能显示出在中风康复中个性化治疗的巨大潜力.
  • 由人工智能驱动的优化康复策略可以改善患者的治疗结果.
  • 人工智能有助于持续的康复,弥合了康复和现实世界功能重整之间的差距.