一项关于拒绝非目标和错误分类运动的研究,用于基于触觉传感器的强大的假肢手掌控制
Hayato Iwai1,2, Feng Wang3
1Graduate School of Engineering, Maebashi Institute of Technology, Maebashi 371-0816, Japan.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
这项研究引入了一种新的方法,通过拒绝无意动作来改善假肢手的控制. 一个对其他拒绝选项 (OvR-RO) 提高了基于触觉传感器的系统的安全性和可靠性.
科学领域:
- 生物医学工程 生物医学工程
- 机器人技术 机器人技术 机器人技术
- 机器学习 机器学习
背景情况:
- 假肢手的控制需要可靠的运动分类,以确保安全性和可用性.
- 来自模糊或非目标运动的意外激活会降低控制和用户安全.
- 基于触觉传感器的方法可以替代表面肌电学,但需要强大的排斥策略.
研究的目的:
- 研究基于触觉传感器的聚乙烯化物 (PVDF) 触觉传感器的假肢控制的计算轻量级运动拒绝机制.
- 为了提高假肢手控制对错误分类和非目标输入的稳定性.
- 为了比较不同拒绝策略的有效性.
主要方法:
- 提出了一种新的无参数决策一致性检查,用于一对其余支向量机器 (OvR-RO),以拒绝对不一致的输出进行分类.
- 将OVR-RO与一类支向量机器 (OCSVM) 的异常值检测和基于的拒绝 (BPNN-Entropy) 进行比较.
- 对模两可的目标试验,未知的动作和非目标身体运动进行评估.
主要成果:
- 对于模两可的动议,OvR-RO在拒绝率和准确性之间取得了有利的平衡,并保持了响应能力.
- 明确拒绝错误分类和非目标动议在提高稳定性方面被证明是有效的.
- 提出的OvR-RO方法在改进基于触觉传感器的假肢控制方面表现有前途.
结论:
- 计算轻量级的运动拒绝策略对于强大的假肢手掌控至关重要.
- OvR-RO机制提供了一种有效的解决方案,用于提高基于触觉传感器的假肢系统的可靠性.
- 进一步开发排斥机制可以显著提高假肢设备的性能和用户安全.
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