A wearable RF sensor on fabric substrate for pulmonary edema monitoring

Muhammad Tayyab; Mohammad S. Sharawi; Atif Shamim

doi:10.1109/SENSET.2017.8125007

A wearable RF sensor on fabric substrate for pulmonary edema monitoring

Muhammad Tayyab, Mohammad S. Sharawi, Atif Shamim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

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.

Original language	English (US)
Title of host publication	2017 Sensors Networks Smart and Emerging Technologies (SENSET)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1-4
Number of pages	4
ISBN (Print)	9781509060115
DOIs	https://doi.org/10.1109/SENSET.2017.8125007
State	Published - Nov 30 2017

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10.1109/SENSET.2017.8125007

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title = "A wearable RF sensor on fabric substrate for pulmonary edema monitoring",

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.",

author = "Muhammad Tayyab and Sharawi, {Mohammad S.} and Atif Shamim",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: 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.",

year = "2017",

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doi = "10.1109/SENSET.2017.8125007",

language = "English (US)",

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AU - Sharawi, Mohammad S.

AU - Shamim, Atif

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: 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.

PY - 2017/11/30

Y1 - 2017/11/30

N2 - 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.

AB - 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.

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DO - 10.1109/SENSET.2017.8125007

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BT - 2017 Sensors Networks Smart and Emerging Technologies (SENSET)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

A wearable RF sensor on fabric substrate for pulmonary edema monitoring

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