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在神经康复中转型建模:催化进步的四个线程

Francisco J Valero-Cuevas^1,2,3, James Finley⁴, Amy Orsborn^5,6,7

¹Alfred E. Mann Department of Biomedical Engineering, University of Southern California, 1042 Downey Way, Los Angeles, 90089, CA, USA. valero@usc.edu.

Journal of neuroengineering and rehabilitation

|April 3, 2024

概括

计算建模通过解决数据需求,多尺度模型,高效算法和现实世界的应用来推进神经康复. 这些策略旨在改善康复工程中的临床转化和患者结果.

科学领域:

神经康复工程神经康复工程
计算神经科学是一种神经科学.
生物医学建模生物医学建模

背景情况:

关于神经康复中建模的变革性机会会议于2023年3月召开专家会议.
该活动的重点是计算建模和神经康复的交集,由国家科学基金会的DARE计划支持.

研究的目的:

讨论神经康复计算建模中的关键问题,挑战和机会.
确定关键领域和共同主题,以促进该领域的发展和改善临床翻译.

主要方法:

围绕四个重点领域组织了讨论:适应和可塑性,个性化,人机交互和"野外"建模.
确定了关键的共同线索,以催化跨不同时间尺度的进展.

主要成果:

强调需要适当的数据策划,用于模型开发和验证.
强调创建跨越个人到人口和细胞到行为层面的多尺度模型.
强调了数据效率高的算法的重要性,并利用现有的传感器进行临床翻译.

结论:

解决数据需求,多尺度建模,高效算法和现实世界的实施是推动神经康复的关键.
这些进展对于将基于模型的治疗方法从研究环境推向临床实践和社区环境至关重要.

关键词:

适应适应适应大数据就是大数据.计算神经科学是一种计算神经科学.会议会议会议会议会议.人与设备的互动.个性化个性化塑性是一种可塑性.康复康复康复康复可穿戴设备可以穿戴.

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