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Real-Time and Noncontact Impulse Radio Radar System for μm Movement Accuracy and Vital-Sign Monitoring Applications

机译:实时和非接触式脉冲无线电雷达系统,用于微米运动精度和生命体征监测应用

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In this paper, a real-time, contactless pulse-based ultra-wideband (UWB) radar sensor was used to precisely detect the movement of the robotic arm, heartbeats, and respiration activities. To increase the object tracking resolution, an algorithm using adaptive and digitalized post-calibration techniques were proposed and tested. Both the radiated and reflected analog pulses were converted to digital signals by a low-noise comparator and its buffer for the time interval and distance detection. Moreover, the dynamic and calibrated tracking mechanism was incorporated into the algorithm for improving tracking accuracy and to continuously localize an object's vibration. The measured performance revealed that the proposed method successfully achieved μm movement precision, thus providing its excellent tracking ability. We performed three different experimental tests to demonstrate the UWB radar's viability. First, the radar was employed to detect the undesired structural vibration of a delta robotic arm, which was subjected to high acceleration and structural flexibility. The measured results indicated that the accuracy of 100 μm can be achieved at a 10 Hz vibration frequency. Next, the apnea alarm was tested, which included an embedded sensitive sensor in the smart mattress in order to execute longterm physiological monitoring. The apnea was mitigated by auto-adjusting the patient's sleeping posture on the mattress when the UWB sensor detected the apnea condition. The final experiment using the radar sensor was to monitor human vital signs, such as heart and breathing rates, simultaneously. In comparison with a commercial electrocardiography instrument, this radar sensor measured 73.2 bpm with only 1.2% deviation. Our results shown that the contactless UWB sensor performs superbly and is well-suited for monitoring physiological parameters.
机译:在本文中,基于实时,非接触式脉冲的超宽带(UWB)雷达传感器用于精确检测机械臂的运动,心跳和呼吸活动。为了提高目标跟踪的分辨率,提出并测试了使用自适应和数字化后校准技术的算法。低噪声比较器及其缓冲区将辐射和反射的模拟脉冲都转换为数字信号,以进行时间间隔和距离检测。此外,将动态且经过校准的跟踪机制并入算法中,以提高跟踪精度并连续定位对象的振动。实测性能表明,该方法成功实现了μm的运动精度,从而提供了出色的跟踪能力。我们进行了三个不同的实验测试,以证明UWB雷达的可行性。首先,雷达被用于检测三角机械臂的不良结构振动,该机械振动受到高加速度和结构灵活性的影响。测量结果表明,在10 Hz的振动频率下可以达到100μm的精度。接下来,对呼吸暂停警报进行了测试,该警报在智能床垫中包括嵌入式敏感传感器,以便执行长期的生理监测。当UWB传感器检测到呼吸暂停状况时,可通过自动调整患者在床垫上的睡眠姿势来缓解呼吸暂停。使用雷达传感器的最终实验是同时监视人类生命体征,例如心脏和呼吸频率。与商用心电图仪相比,此雷达传感器的测量值为73.2 bpm,偏差仅为1.2%。我们的结果表明,非接触式UWB传感器性能出色,非常适合监测生理参数。

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