闭环假肢控制的神经计算建模
概括
这项研究调查了个人如何学习控制假肢握力. 增加的目标力和电机噪声降低了控制精度,而感觉噪声没有显著影响,告知了更好的人与假肢的相互作用.
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.
- 人与计算机的交互
背景情况:
- 肌电上肢假肢在可用性和高排斥率方面面临挑战.
- 人工感官反可以增强人 - 假肢接口,提高性能和用户体验.
- 缺少一种原则性的方法来评估假肢中感官反的影响和有效性.
研究的目的:
- 调查受试者如何在视觉指导下学会控制假肢握力.
- 检查目标抓力,感觉噪声和电机噪声对控制性能的影响.
- 开发一种计算模型,用于理解假肢控制中的学习.
主要方法:
- 收集了从20名非残疾人进行抓取任务的实验数据.
- 在任务中操纵目标抓力,感觉噪音和电机噪音.
- 开发了一个计算模型,将学习描述为获得内部假肢模型.
主要成果:
- 随着目标力和电机噪声的增加,控制精度下降.
- 感觉噪声没有显著影响控制精度.
- 计算模型对实验结果进行了定性复制,特别是对电机噪声的影响.
结论:
- 发动机噪声显著影响假肢握力控制精度.
- 开发的模型为了解假肢用户行为提供了一个基本步骤.
- 这项研究有助于开发更好的闭环控制策略,用于上肢假肢.
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