一种基于类型-2模糊推理的方法使得步行速度的估计能够适应个人间的步行模式
Linrong Li1, Wenxiang Liao1, Hongliu Yu1
1Institute of Rehabilitation Engineering and Technology, 47863 University of Shanghai for Science and Technology , Shanghai, China.
Biomedizinische Technik. Biomedical engineering
|November 25, 2024
概括
这项研究引入了一种新的方法,通过分析大腿运动来准确估计步行速度. 该系统适应个人步行模式,改善了康复机器人和假肢的控制.
科学领域:
- 生物力学 生物力学
- 机器人技术 机器人技术 机器人技术
- 信号处理 信号处理
背景情况:
- 步行速度由步骤频率 (SF) 和步伐长度 (SL) 调节.
- 现有的速度估计方法往往忽略了这些个别的监管策略.
- 适应不同的步行模式对于有效的人机交互至关重要.
研究的目的:
- 开发一种准确的步行速度估计方法.
- 创建一个适应个人间速度调节策略的系统.
- 为了使步态独立的速度估计.
主要方法:
- 使用单个安装在大腿上的IMU,提取大腿特征.
- 采用间隔类型-2模糊推断系统来推断速度调节的意图.
- 通过在跑步机上使用各种速度和步态模式的五个受试者验证了该方法.
主要成果:
- 实现了0.0704 ± 0.0087 m/s的整体根平均平方误差 (RMSE),用于速度估计.
- 在不同的步态模式中保持低RMSE (≤0.074±0.005米/秒).
- 对肢体长度和步行习惯的变化表现出强度.
结论:
- 拟议的方法提供了高精度的步行速度估计.
- 它可以适应各种脚-四肢 (FL) 组合,而无需单独调整.
- 潜在的应用包括用于康复机器人和下肢假肢的直观速度适应控制.
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