This paper presents the design and the development of a Battery Assisted Passive Radio-Frequency IDentification (RFID) tag in the Ultra High-Frequency band integrated with inertial measurement unit (IMU) sensors tested for the biomechanical analysis of human body movements. Enhanced by a compact and efficient meandered Planar Inverted-F Antenna (PIFA), the device exploits a specific RFID chip having a dual-access -wired and wireless- to the memory. A properly decoupled cell battery is also foreseen to boost the chip sensitivity and to supply power to an ultra-low power microcontroller and to the sensors. The device has been realized using off-the-shelf low-cost discrete components on FR4 substrate, validated, and tested in capturing real human movements. Two sensor-tags have been applied on the pelvis and on the torso of an individual moving in front of the RFID Reader antenna. Afterward, sensor data have been collected, processed, and filtered with specific algorithms, and used to control a musculoskeletal virtual model in the OpenSense software tool. The results show that the whole system correctly reproduces the performed movements, demonstrating the appropriateness of the proposed RFID-sensor in wireless movement capture applications.
Design of UHF RFID Sensor-Tags for the Biomechanical Analysis of Human Body Movements
Colella R.Primo
;Catarinucci L.Ultimo
2021-01-01
Abstract
This paper presents the design and the development of a Battery Assisted Passive Radio-Frequency IDentification (RFID) tag in the Ultra High-Frequency band integrated with inertial measurement unit (IMU) sensors tested for the biomechanical analysis of human body movements. Enhanced by a compact and efficient meandered Planar Inverted-F Antenna (PIFA), the device exploits a specific RFID chip having a dual-access -wired and wireless- to the memory. A properly decoupled cell battery is also foreseen to boost the chip sensitivity and to supply power to an ultra-low power microcontroller and to the sensors. The device has been realized using off-the-shelf low-cost discrete components on FR4 substrate, validated, and tested in capturing real human movements. Two sensor-tags have been applied on the pelvis and on the torso of an individual moving in front of the RFID Reader antenna. Afterward, sensor data have been collected, processed, and filtered with specific algorithms, and used to control a musculoskeletal virtual model in the OpenSense software tool. The results show that the whole system correctly reproduces the performed movements, demonstrating the appropriateness of the proposed RFID-sensor in wireless movement capture applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
