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Statistical analytics of wearable passive RFID-based biomedical textile monitors for real-time state classification

机译:基于可穿戴式RFID的生物医学纺织监测器的统计分析,用于实时状态分类

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Wearable smart devices have become ubiquitous, with powered devices capable of collecting real-time biometric information from its users. Typically, these devices require a powered component to be worn and maintained, such as a battery-powered sensor, Bluetooth communications device, or glasses. Pregnancy and infant monitoring devices may be uncomfortable to the mother or baby and are subject to signal loss if the patient changes position or becomes mobile because the device must remain tethered to the patient by a belt and plugged into a wall for power. Our wearable, wireless, smart garment devices are knitted into the fabric using conductive thread to which a Radio Frequency Identification (RFID) chip within the fabric is inductively coupled. Our work utilizes the Received Signal Strength Indication (RSSI), which changes as the knitted antenna is deformed due to stretching of the garment, to determine different types of motion in the inductively-coupled chip and knit antenna structure as it is moved by the wearer.
机译:可穿戴智能设备已变得无处不在,有能力从其用户收集实时生物识别信息的供电设备。通常,这些装置需要佩戴和维护的动力部件,例如电池供电的传感器,蓝牙通信设备或眼镜。怀孕和婴儿监测装置对母婴可能不舒服,如果患者改变位置或变得移动,则经过信号损失,因为该装置必须通过皮带保持在患者身上并插入墙壁以供电。我们可穿戴的无线智能服装装置使用导电线针织成织物,织物内的射频识别(RFID)芯片是电感耦合的。我们的作品利用所接收的信号强度指示(RSSI),随着衣服的拉伸,当针织的天线变形时变化,以确定电感耦合芯片中的不同类型的运动,并且在穿着者移动时,针织天线结构。

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