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
  • [41] Glabella: Continuously sensing blood pressure behavior using an unobtrusive wearable device
    Holz, Christian
    Wang, Edward
    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2017, 1 (03)
  • [42] Smart Insole: A Wearable Sensor Device for Unobtrusive Gait Monitoring in Daily Life
    Lin, Feng
    Wang, Aosen
    Zhuang, Yan
    Tomita, Machiko R.
    Xu, Wenyao
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (06) : 2281 - 2291
  • [43] A Wearable Accelerometer System for Unobtrusive Monitoring of Parkinson's Diease Motor Symptoms
    Khan, Faisal M.
    Barnathan, Michael
    Montgomery, Michael
    Myers, Stanely
    Cote, Lucien
    Loftus, Sheree
    2014 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE), 2014, : 120 - 125
  • [44] Utilizing Consumer-grade Wearable Sensors for Unobtrusive Rehabilitation Outcome Prediction
    Conci, Jason
    Sprint, Gina
    Cook, Diane
    Weeks, Douglas
    2019 IEEE EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL & HEALTH INFORMATICS (BHI), 2019,
  • [45] PERSISTENT EFFUSION OF KNEE JOINT
    GOLDNER, JL
    JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1967, 202 (11): : 1060 - &
  • [46] A Wearable System Based on Flexible Sensors for Unobtrusive Respiratory Monitoring in Occupational Settings
    Di Tocco, Joshua
    Presti, Daniela Lo
    Zaltieri, Martina
    D'Alesio, Giacomo
    Filosa, Mariangela
    Massari, Luca
    Aliperta, Andrea
    Di Rienzo, Marco
    Carrozza, Maria Chiara
    Ferrarin, Maurizio
    Massaroni, Carlo
    Oddo, Calogero Maria
    Schena, Emiliano
    IEEE SENSORS JOURNAL, 2021, 21 (13) : 14369 - 14378
  • [47] Design of Unobtrusive Wearable Mental Stress Monitoring Device Using Physiological Sensor
    Salafi, T.
    Kah, J. C. Y.
    7TH WACBE WORLD CONGRESS ON BIOENGINEERING 2015, 2015, 52 : 11 - 14
  • [48] An ECG-on-Chip with Joint QRS Detection & Data Compression for Wearable Sensors
    Deepu, C. J.
    Zhang, X. Y.
    Wong, D. L. T.
    Lian, Y.
    2016 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2016, : 2908 - 2908
  • [49] Wearable Fiber Optic Sensors for Biomechanical Sensing via Joint Angle Detection
    D'Mello, Yannick
    Skoric, James
    Moukarzel, Lea
    Hakim, Siddiqui
    Plant, David, V
    2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2019, : 3221 - 3225
  • [50] Fall Detection with Unobtrusive Infrared Array Sensors
    Fan, Xiuyi
    Zhang, Huiguo
    Leung, Cyril
    Shen, Zhiqi
    MULTISENSOR FUSION AND INTEGRATION IN THE WAKE OF BIG DATA, DEEP LEARNING AND CYBER PHYSICAL SYSTEM, 2018, 501 : 253 - 267