Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

Design of UHF RFID Sensor-Tags for the Biomechanical Analysis of Human Body Movements

Academic Article
Publication Date:
2021
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.
Iris type:
01.01 Articolo in rivista
Keywords:
Inertial sensors; Motion analysis; Planar Inverted-F Antenna; RFID Sensor-tag; UHF technology
List of contributors:
Tumolo, MARIA ROSARIA; Leo, CARLO GIACOMO; Sabina, Saverio; Guarino, Roberto; Mincarone, Pierpaolo; Colella, Riccardo
Authors of the University:
COLELLA RICCARDO
GUARINO ROBERTO
LEO CARLO GIACOMO
MINCARONE PIERPAOLO
SABINA SAVERIO
Handle:
https://iris.cnr.it/handle/20.500.14243/426784
Published in:
IEEE SENSORS JOURNAL
Journal
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.2.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)