An RFID-based Human Spine Behavior Monitor Method

被引:0
|
作者
Wang, Honggang [1 ]
Liu, Weiwang [1 ]
Xu, Xueni [1 ]
Pang, Meng [1 ]
Pang, Shengli [1 ]
Pan, Ruoyu [1 ]
机构
[1] Sch Xian Univ Posts & Telecommun, Xian 710121, Shaanxi, Peoples R China
关键词
contact spinal sign monitoring; human spine motion model; RFID; backscatter;
D O I
10.1109/ICNLP60986.2024.10692562
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The spine is an important component of the human skeletal system, playing a crucial role in maintaining balance, facilitating movement, and protecting the nervous system. This paper presents a method for monitoring human spinal behavior using ultra-high frequency passive RFID(Radio Frequency Identification) technology. This method aims to predict the occurrence and changes of diseases, providing earlier health interventions. The study summarizes the geometric principles underlying human spine physiological movements and designs corresponding models to capture spine motion patterns. A RFID phase data preprocessing framework is devised to address the phase periodicity, p ambiguity, and multipath interference issues commonly encountered when collecting physical layer data with COTS RFID readers, enabling more accurate restoration of phase data. Additionally, a spine bending angle prediction model based on polar coordinates is developed to mitigate the phase interference caused by tag rotation during motion. Experimental results demonstrate that this method can monitor human spine behavior without distance limitations, in everyday environments, without requiring individuals to wear complex sensor devices. Furthermore, the method exhibits robust monitoring performance and accuracy even in complex scenarios.
引用
收藏
页码:542 / 551
页数:10
相关论文
共 50 条
  • [31] RFID-based Intelligent Warehouse Management
    Gao, Yu
    Lin, Chun
    2018 INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATIONS AND MECHATRONICS ENGINEERING (CCME 2018), 2018, 332 : 27 - 31
  • [32] RFID-based optimisation of Kanban processes
    Scholz-Reiter, Bernd
    Gorldt, Christian
    Hinrichs, Uwe
    Tervo, Jan Topi
    Krieg, Georg
    PPS MANAGEMENT, 2007, 12 (01): : 55 - 57
  • [33] RFID-Based Attendance Management System
    Nguyen, H. K.
    Chew, M. T.
    PROCEEDINGS OF THE 2017 2ND WORKSHOP ON RECENT TRENDS IN TELECOMMUNICATIONS RESEARCH (RTTR), 2017, : 74 - 79
  • [34] The RFID-Based Manufacturing and Inventory Revolution
    HAMIDULLH Khan Niazi
    RIAZ Ahmed
    SHAHID Ikramullah Butt
    CADDM, 2005, (01) : 46 - 51
  • [35] An RFID-based object IocaIisation framework
    Chawla K.
    Robins G.
    International Journal of Radio Frequency Identification Technology and Applications, 2011, 3 (1-2) : 2 - 30
  • [36] SixthSense: RFID-based Enterprise Intelligence
    Ravindranath, Lenin
    Padmanabhan, Venkata N.
    Agrawal, Piyush
    MOBISYS'08: PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS, AND SERVICES, 2008, : 253 - 266
  • [37] RFID-based Monitoring of Human Operators for Safety in Outdoor Working Sites
    Tavanti, Emanuele
    Motroni, Andrea
    Buffi, Alice
    Nepa, Paolo
    Pirozzi, Marco
    Di Donato, Luciano
    Tomassini, Laura
    Ferraro, Alessandra
    2023 IEEE 13TH INTERNATIONAL CONFERENCE ON RFID TECHNOLOGY AND APPLICATIONS, RFID-TA, 2023, : 205 - 208
  • [38] ClothFace: A Passive RFID-Based Human-Technology Interface on a Shirtsleeve
    Mehmood, Adnan
    He, Han
    Chen, Xiaochen
    Vianto, Aleksi
    Vianto, Ville
    Buruk, Oguz 'Oz'
    Virkki, Johanna
    ADVANCES IN HUMAN-COMPUTER INTERACTION, 2020, 2020
  • [39] Passive RFID-based Textile Touchpad
    He, Han
    Chen, Xiaochen
    Raivio, Leevi
    Huttunen, Heikki
    Virkki, Johanna
    2020 14TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP 2020), 2020,
  • [40] RFID-based Driving Fatigue Detection
    Yang, Chao
    Wang, Xuyu
    Mao, Shiwen
    2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,