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Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography
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基于RFID反射的运动运动运动传感器使用基于ECOC的SVM.

Lei Han1, Xia Hua1

  • 1Department of Physical Education, China University of Petroleum (East China), Qingdao 266580, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种RFID反射波运动传感方案,使用接收信号强度和支持矢量机 (SVM) 来准确识别多类动作,这对物联网至关重要.

关键词:
背部散射器是一种背部散射器.运动感应 运动感应 感应无线电频率识别方式支持矢量机器的支持矢量机器.

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科学领域:

  • * 计算机科学 计算机科学
  • * 电气工程 电气工程
  • * * 信号处理 信号处理

背景情况:

  • *射频识别 (RFID) 是物联网 (IoT) 和万物互联网 (IoE) 的关键技术,特别是在5G时代.
  • *基于RFID的运动传感是一个新兴的研究领域,具有各种应用的巨大潜力.
  • *在当前的传感技术中,对各种运动姿势的准确分类仍然是一个挑战.

研究的目的:

  • *为体育运动运动传感提出一种新的RFID反射散射方案.
  • * 应对不同行动的多重分类所带来的挑战.
  • *使用机器学习技术实现高分类准确性.

主要方法:

  • * 利用RFID反射散射技术来捕获运动数据.
  • * 作为一个功能,从反向散射的RFID信号中获得的Employed Received Signal Strength (RSS).
  • * 实现基于输出编码 (ECOC) 的纠错输出编码支持矢量机 (SVM) 进行多类分类.

主要成果:

  • *收集了与各种动作姿势相对应的信号强度.
  • *通过广泛的实验证明了拟议方案的有效性.
  • * 通过使用SVM算法,实现了不同运动运动的高分类精度.

结论:

  • * 拟议的RFID反射散射方案对体育运动运动传感有效.
  • * RSS 和基于 ECOC 的 SVM 的组合为多重分类问题提供了强大的解决方案.
  • * 这项技术有望通过增强的运动识别来推进物联网和IoE应用.