Wearable Loops for Unobtrusive Electromagnetic Detection of Joint Effusion

被引:0
|
作者
Dalisky, Zeke Z. [1 ]
Mishra, Vigyanshu [1 ]
Kiourti, Asimina [1 ]
机构
[1] Ohio State Univ, Dept Elect & Comp Engn, ElectroSci Lab, Columbus, OH 43210 USA
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Joint effusion is associated with synovial fluid build-up in or around a joint. Current state-of-the-art medical imaging methods such as X-ray, ultrasound, and Magnetic Resonance Imaging (MRI) can provide high-resolution images but are resource-intensive and limited to specialized medical facilities, preventing them from being used for long-term, continuous and real-time monitoring. In this work, we propose an alternative, wearable method for detecting joint effusion which addresses these shortcomings. The method relies on monitoring changes in the transmission coefficient (S-21) between two conducting loops placed around the limb near the joint region. Using electromagnetic simulations on a simplified arm-effusion model, a clear trend is presented between the magnitude/phase of S-21 and effusion radius. Particularly, for the best design, 0.5-cm variations from 1 to 3 cm in spherical effusion radius can be detected with a minimum required S-21 precision of 1.02 dB for magnitude or/and 13.50 degrees for phase. Significance of this approach lies in early stage detection and ease of treatment for such medical conditions.
引用
收藏
页码:169 / 170
页数:2
相关论文
共 50 条
  • [1] A Wearable System for Unobtrusive Mood Detection
    Lietz, Rebecca
    Harraghy, Meaghan
    Brady, James
    Calderon, Diane
    Cloud, Joe
    Makedon, Fillia
    12TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS (PETRA 2019), 2019, : 329 - 330
  • [2] Detection of joint effusion on radiographs of horses
    Lawson, J. S.
    Bolt, D. M.
    May, S.
    Smith, A. J.
    Felstead, C. W.
    Weller, R.
    VETERINARY RECORD, 2012, 170 (13) : 336 - U46
  • [3] Wearable Loops for Dynamic Monitoring of Joint Flexion: A Machine Learning Approach
    Saltzman, Henry
    Rajaram, Rahul
    Zhang, Yingzhe
    Islam, Md Asiful
    Kiourti, Asimina
    ELECTRONICS, 2024, 13 (12)
  • [4] The effectiveness of sonography in detection of hip joint effusion
    Weybright, PN
    Murry, KH
    Jacobson, JA
    Lin, J
    Fessell, DP
    Jamadar, DA
    RADIOLOGY, 2001, 221 : 118 - 118
  • [5] Wearable sensing devices for unobtrusive biomedical monitoring
    Fujii, Koji
    IEEE CPMT SYMPOSIUM JAPAN 2015, (ICSJ 2015), 2015, : 204 - 207
  • [6] Unobtrusive Sensing and Wearable Devices for Health Informatics
    Zheng, Ya-Li
    Ding, Xiao-Rong
    Poon, Carmen Chung Yan
    Lo, Benny Ping Lai
    Zhang, Heye
    Zhou, Xiao-Lin
    Yang, Guang-Zhong
    Zhao, Ni
    Zhang, Yuan-Ting
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2014, 61 (05) : 1538 - 1554
  • [7] GestureWrist and GesturePad: Unobtrusive wearable interaction devices
    Rekimoto, J
    FIFTH INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS, PROCEEDINGS, 2001, : 21 - 27
  • [8] Unobtrusive and Multimodal Wearable Sensing to Quantify Anxiety
    Zheng, Yali
    Wong, Tracy C. H.
    Leung, Billy H. K.
    Poon, Carmen C. Y.
    IEEE SENSORS JOURNAL, 2016, 16 (10) : 3689 - 3696
  • [9] Unobtrusive and Wearable Systems for Automatic Dietary Monitoring
    Prioleau, Temiloluwa
    Moore, Elliot, II
    Ghovanloo, Maysam
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2017, 64 (09) : 2075 - 2089
  • [10] Machine Learning-Based Unobtrusive Intake Gesture Detection via Wearable Inertial Sensors
    Al Jlailaty, Hussein
    Celik, Abdulkadir
    Mansour, Mohammad M.
    Eltawil, Ahmed M.
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2023, 70 (04) : 1389 - 1400