投影新身体:在学习与可穿戴机器人一起走路时,身体形象如何演变
I-Chieh Lee1,2, Huan Min1,2,3, Ming Liu1,2
1Lampe Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA.
PNAS nexus
|February 19, 2026
概括
学习用机器人腿走路可以改善步态和身体感知,但感知和实际运动之间的差距仍然存在. 增强感官反和校准身体形象是有效的可穿戴机器人训练的关键.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 神经科学是一个神经科学.
- 人与计算机的交互
背景情况:
- 可穿戴机器人挑战了人类运动系统的传统定义.
- 对于可穿戴机器人如何在动态运动期间影响用户的身体形象的理解有限.
研究的目的:
- 为了检查在学习用机器人腿行走时感知身体形象的变化.
- 调查多天训练期间身体形象和步行表现的共同演变.
主要方法:
- 使用感知运动系数测量步行表现和感知身体形象.
- 应用人类运动学习理论到佩戴机器人系统.
- 与使用机器人腿的人进行了为期几天的培训课程.
主要成果:
- 运动学习改善了身体和感知步行模式,将机器人腿集成到传感运动系统中.
- 观察到感知和实际运动之间的持续差异,可能是由于缺少假肢感觉.
- 在以后的会议中,感知过度估计可能会阻碍进一步的运动改善.
结论:
- 可穿戴机器人训练可以改善协调,但强调需要增强感官反和身体图像校准.
- 解决感知-行动差距对于优化培训和开发有效的嵌入式辅助技术至关重要.
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