一种基于主动扭矩预测模型的上肢外骨架实时控制方法
Sujiao Li1,2,3, Lei Zhang1,2, Qiaoling Meng1,2,3
1Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China.
Bioengineering (Basel, Switzerland)
|December 23, 2023
概括
这项研究引入了一种新的实时控制方法,用于上肢外骨架机器人,增强中风康复. 该系统使用主动扭矩预测和可调节的辅助来实现个性化和有效的患者恢复.
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
- 神经康复疗法 神经康复疗法
背景情况:
- 外骨机器人对于中风患者康复至关重要.
- 用积极运动意图进行训练可以改善康复结果.
- 个性化和精确的康复对于中风恢复至关重要.
研究的目的:
- 建议使用主动扭矩预测模型对上肢外骨实时控制方法.
- 通过可调节的助力比率来实现个性化和精确的康复.
- 在外骨架辅助疗法中增强人机交互.
主要方法:
- 开发了一种用于上肢外骨架的活跃扭矩预测模型.
- 使用电肌图 (EMG) 信号和肘角作为控制输入.
- 训练了一个反向传播 (BP) 神经网络,用于特征提取和扭矩预测.
- 在PC和嵌入式系统上实现了该模型.
主要成果:
- 活跃扭矩预测模型在PC和嵌入式系统上表现出高精度.
- 在嵌入式系统上实现了0.1956 N·m的根平均平方误差 (RMSE) 和94.98%的准确性.
- 实时控制系统表现出40毫秒的低延迟.
结论:
- 拟议的方法为上肢外骨架提供了准确有效的实时控制.
- 可调节的助力比率允许个性化康复.
- 低系统延迟提高了中风康复中人与计算机交互的适应性和有效性.
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