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首页> 外文期刊>IEEE transactions on mobile computing >Motion-Fi^++: Recognizing and Counting Repetitive Motions With Wireless Backscattering
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Motion-Fi^++: Recognizing and Counting Repetitive Motions With Wireless Backscattering

机译:Motion-Fi ^ ++:通过无线反向散射识别和计算重复动作

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摘要

Driven by a wide range of real-world applications, several ground-breaking RF-based motion-recognition systems were proposed to detect and/or recognize macro/micro human movements. These systems often suffer from various interferences caused by multiple-users moving simultaneously, resulting in extremely low recognition accuracy. Even if the repetitive motions are fairly well detectable through the wireless signals in theory, in reality they get blended into various other system noises during the motion. Moreover, irregular motion patterns among users will lead to expensive computation cost for motion recognition. To tackle these challenges, we propose a novel wireless sensing system, called Motion-Fi thorn, which marries battery-free wireless backscattering and device-free sensing in one clean sheet. Motion-Fi thorn is an accurate, interference tolerable motion-recognition system, which counts repetitive motions without using scenario-dependent templates or profiles and enables multi-user performing certain motions simultaneously because of the relatively short transmission range of backscattered signals and dedicated signal separation method. We implement a backscattering wireless platform to validate our design in various scenarios for over 6 months when different persons, distances and orientations are incorporated. In our experiments, the periodicity in motions could be recognized without any learning or training process, and the accuracy of counting such motions can be achieved within 5 percent count error. With little efforts in learning the patterns, our method could achieve 95.2 percent motion-recognition accuracy for a variety of 7 typical motions. Moreover, by leveraging the periodicity of motions, the recognition accuracy could be further improved to nearly 100 percent with only three repetitions. Our experiments also show that the motions of multiple persons separating by around 2 meters cause little accuracy reduction in the counting process.
机译:由广泛的现实应用驱动,提出了几种基于接地的基于RF的运动识别系统来检测和/或识别宏/微人人运动。这些系统经常遭受由多用户同时移动引起的各种干扰,从而产生极低的识别精度。即使在理论上通过无线信号是相当良好地检测到的重复运动,实际上它们也会在运动期间被混合成各种其他系统噪声。此外,用户之间的不规则运动模式将导致运动识别的昂贵的计算成本。为了解决这些挑战,我们提出了一种名为Motion-Fi刺的新型无线传感系统,它在一个干净的纸张中使用无电池无线反响和无设备感应。 Motion-Fi刺是一种准确的干扰可容忍的运动识别系统,它在不使用场景依赖的模板或配置文件的情况下计算重复动作,并且由于反向散射信号的传输范围和专用信号分离的传输范围相对短的传输范围,并且可以同时执行多用户执行某些运动方法。我们实现了一个反向散射无线平台,以在不同的人员,距离和方向结合到不同的情况下在各种场景中验证我们的设计。在我们的实验中,可以在没有任何学习或培训过程的情况下识别动作的周期性,并且可以在5%的计数误差内实现计数这些动作的准确性。对于学习模式的努力很少,我们的方法可以实现95.2%的运动识别精度,适用于各种7个典型运动。此外,通过利用运动的周期性,识别准确度可以进一步提高到几乎100%,只有三个重复。我们的实验还表明,多个分离2米的多人的动作在计数过程中略微减少。

著录项

  • 来源
    《IEEE transactions on mobile computing》 |2021年第5期|1862-1876|共15页
  • 作者单位

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Peoples R China;

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Peoples R China;

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Peoples R China;

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Peoples R China;

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Peoples R China;

    Illinois Inst Technnol Dept Comp Sci Chicago IL 60616 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Wireless sensing; wireless backscattering;

    机译:无线传感;无线反向散射;

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