一个实时预测姿势控制系统,具有温度反.
Yaoyu Duan1, Huimin Jiao2, Dangxiao Wang3
1Department of Mechanical and Electrical Engineering, Beijing Institute of Graphic Communication, Beijing, 102600, China.
Scientific reports
|July 31, 2025
概括
本研究介绍了一种使用长短期记忆 (LSTM) 网络的智能传感器系统,用于增强热生物反,以改善实时的平衡校正和姿势稳定性.
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
- 可穿戴技术可穿戴技术
背景情况:
- 均衡的姿势对于运动,康复和机器人技术至关重要.
- 热生物反增强了姿势稳定性,特别是对于感觉受损的个体.
- 传统的热生物反系统遭受缓慢的温度调整和延迟的反应.
研究的目的:
- 设计一个智能传感器系统,实时进行平衡校正和姿势稳定.
- 提高热生物反系统的响应能力.
- 通过预测性热触觉反来增强姿势控制.
主要方法:
- 使用惯性传感器测量身体倾斜角度.
- 开发了一个可穿戴的温度控制模块,用于生物反.
- 实现了一个长期短期记忆 (LSTM) 神经网络,具有用于姿势预测的滑动窗口.
- 雇员交叉验证以优化LSTM模型培训.
主要成果:
- 该LSTM网络准确地使用角度和加速数据预测了姿势变化.
- 与传统方法相比,该系统可以更及时地调整温度.
- 通过Romberg站立倾斜测试,显著提高了平衡能力.
结论:
- 拟议的系统有效地改善了实时平衡校正和姿势稳定性.
- 使用LSTM的预测性热生物反比传统方法提供了显著的进步.
- 这项技术有望用于体育训练,康复和辅助机器人的应用.
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