在线适应框架使得受中风影响的患者在运动期间可以个性化外骨辅助
Inseung Kang1, Dean D Molinaro2, Dongho Park3
1Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213 USA.
IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society
|September 17, 2025
概括
这项研究引入了一种自适应式机器人外骨控制器,为下肢残疾用户提供个性化的步行辅助. 该框架快速适应个人用户,改善移动性并降低代谢成本.
科学领域:
- 生物医学工程 生物医学工程
- 康复机器人 康复机器人
- 人与机器人的交互
背景情况:
- 机器人外骨架为下肢残疾人提供了显著的移动性改善.
- 由于可变的用户步态动态,控制器性能下降阻碍了广泛采用.
- 现有的控制器很难适应不同的用户和环境.
研究的目的:
- 为机器人外骨控制器开发一个在线适应框架.
- 为了实现持续的,实时的模型更新,以提供个性化的步行辅助.
- 为了证明模型在不同外骨硬件上的可转移性.
主要方法:
- 实施了在线适应框架,使用实时数据流来更新用户状态估计模型.
- 开发了一种传感器信号转换技术,用于跨硬件模型传输.
- 验证了对有能力的受试者,中风幸存者和商业外骨架设备的框架.
主要成果:
- 在适应后一分钟内,在步行阶段估计方面取得了显著改善 (40.9%的健身者,65.9%的中风幸存者).
- 与基线模型相比,扭矩配置错误减少了32.7%.
- 试点测试显示,中风幸存者的步行速度增加了21.8%,代谢成本减少了6.5%.
结论:
- 拟议的在线适应框架可以实现个性化的机器人外骨控制.
- 该方法增强了步行阶段估计,并减少了控制错误.
- 初步结果表明,在康复环境中改善临床结果和用户体验的潜力.
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