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

Abstract

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.