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    A wearable RF sensor on fabric substrate for pulmonary edema monitoring

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    Type
    Conference Paper
    Authors
    Tayyab, Muhammad
    Sharawi, Mohammad S.
    Shamim, Atif cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2017-11-30
    Permanent link to this record
    http://hdl.handle.net/10754/626615
    
    Metadata
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    Abstract
    We propose a radio frequency (RF) sensor built on a fabric textile substrate for pulmonary edema monitoring. The 37-port RF sensor is designed and optimized to operate at 60 MHz with a low input power of 1 mW. By applying the least squares (LS) method, an equation was obtained for dielectric constant estimation using the transmission coefficient of each RF sensor port. The simulated errors are estimated for normal lung, edema and emphysema infected lung cases using a human chest model with an average error of 0.57%. Inkjet printing of the proposed design is then discussed.
    Citation
    Tayyab M, Sharawi MS, Shamim A (2017) A wearable RF sensor on fabric substrate for pulmonary edema monitoring. 2017 Sensors Networks Smart and Emerging Technologies (SENSET). Available: http://dx.doi.org/10.1109/SENSET.2017.8125007.
    Sponsors
    This project was funded by the National Plan for Science, Technology and Innovation (Maarifah) - King Abdulaziz City for Science and Technology - through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM) - the Kingdom of Saudia Arabia, under grant number 15-MED-3742-04. The authors would like to thank King Abdullah University of Science and Technology (KAUST) for their support in fabrication and experimental validation of the proposed sensor.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2017 Sensors Networks Smart and Emerging Technologies (SENSET)
    DOI
    10.1109/SENSET.2017.8125007
    Additional Links
    http://ieeexplore.ieee.org/document/8125007/
    ae974a485f413a2113503eed53cd6c53
    10.1109/SENSET.2017.8125007
    Scopus Count
    Collections
    Conference Papers; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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