在假肢手的设计中,合并运动神经元和姿势协同作用,以实现自然的生物接口
Patricia Capsi-Morales1, Deren Y Barsakcioglu2, Manuel G Catalano3
1Department of Computer Engineering, Technical University of Munich (TUM), Munich, Germany.
Science robotics
|January 15, 2025
概括
这项研究引入了一种新的控制方法,通过结合姿势协同作用和神经解码来控制机器人四肢. 这种方法可以更自然,更准确地控制假肢手,大大提高了用户的灵敏度.
科学领域:
- 生物医学工程 生物医学工程
- 神经科学是一个神经科学.
- 机器人技术 机器人技术 机器人技术
背景情况:
- 目前的机器人四肢控制缺乏自然性和灵巧性.
- 生物体重建的进步受到控制接口的限制.
研究的目的:
- 开发和验证一种控制方法,将姿势协同作用和神经解码结合起来,用于假肢手.
- 为了增强机器人肢体应用中的自然控制和灵敏度.
主要方法:
- 根据两个姿势协同作用,开发了一只具有两种功率的柔软假肢手.
- 研究将神经指令映射到姿势协同作用,使用神经解码脊柱运动神经元活动.
- 实施了一种在线方法,用于对假肢手的持续控制.
主要成果:
- 与经典的肌肉协同相比,神经协同显示出更高的维度和强度.
- 结合的神经和姿势协同作用,使协调的多位数动作能够精确,自然地控制,达到机械分组的> 90%.
- 假肢使用者显示神经协同效应 (82.5%) 与肌肉协同效应 (35.0%) 的目标命中率显著更高.
结论:
- 多协同机器人手和神经解码算法的联合设计可促进自然的模块化控制.
- 这种方法使得灵巧的任务,包括手动操作,以前是不可行的.
- 这些发现为更直观,更有效的假肢控制提供了途径.
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