神经工程方法评估中风中运动下降路径的结构和功能变化
Jordan N Williamson1, Rita Huan-Ting Peng1, Joohwan Sung1
1University of Illinois at Urbana-Champaign, 1406 W. Green Street, Urbana, Urbana, Illinois, 61801-3028, UNITED STATES.
Progress in biomedical engineering (Bristol, England)
|August 22, 2025
概括
脑卒中患者往往因为运动路径受损而面临终身运动障碍. 目前评估这些变化的方法缺乏突破,强调需要先进的人工智能和数据集成来改善中风康复.
科学领域:
- 神经科学
- 康复医学
- 生物医学工程
背景情况:
- 脑卒中是导致成年人残疾的主要原因,
- 超过60%的中风幸存者经历长期运动障碍,影响日常活动和独立性.
- 这些残疾源于运动下降路径的结构和功能变化,包括皮质脊髓 (CST).
研究的目的:
- 审查当前的神经成像,神经调节和电生理技术,以评估中风后的运动下降途径变化.
- 确定现有评估方法的局限性和挑战性.
- 倡导整合人工智能 (AI) 和大型多模式数据注册表,以改善临床实践.
主要方法:
- 对神经成像技术 (例如扩散张力成像) 的最新进展进行审查.
- 对神经调节策略的分析 (例如,跨磁刺激).
- 电生理学方法的评估 (例如,运动唤起的潜能).
主要成果:
- 在量化评估运动路径变化方面取得了显著进展.
- 现有技术在临床实用性和突破潜力方面存在局限性.
- 未来发展需要人工智能和全面的数据注册表.
结论:
- 目前用于评估中风后运动路径变化的神经工程方法需要进一步发展.
- 人工智能和大型多模式数据对于中风预后和治疗的范式转变至关重要.
- 要将这些技术融入中风幸存者的标准临床护理中,
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