Abstract
The patch antennas in wireless networks of the body are widely used in the health sector and for the monitoring of a person, for the diagnosis and control of diseases. Its applicability is due to its small size and its low power, but designing this type of antennas has some disadvantages, since by contacting the human body it is very difficult to transmit the data correctly. Therefore, a slot-ultra-wideband (S-UWB) patch antenna will be analyzed and designed for applications in biomedicine that were used in the UWB wireless body area network (WBAN) and where its reliability is tested. Its frequency of operation is 4.9 and 7.1 GHz. The dimensions of the S-UWB patch antenna are 27 mm × 27 mm × 1.1 mm. This antenna was designed and simulated to verify the results of the measurements. The S-UWB has been simulated with a mathematical software to obtain the possible results.
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Acknowledgments
This research was supported by the Telecommunications and telematics Investigation Group (GITEL for its acronym in Spanish) and the teachers of Electronic Engineering of the Salesian Polytechnic University who provided insight and expertise that greatly assisted the research, although they may not agree with all the interpretations of this paper. We would also like to show our gratitude to Diego Cuji for sharing his pearls of wisdom with us during the course of this research, and we thank to all our classmates for their ideas that helped us developing this paper in a proper way. We are also immensely grateful to Juan Pablo Bermeo and Paúl Chazi for their comments on an earlier version of the manuscript, although any errors are our own and should not tarnish the reputations of these esteemed persons. Engineering gives us the opportunity to learn many things and to engineer others, so engineering students or engineers have the obligation to look for solutions and help our society to get ahead.
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Procel-Feijóo, J., Chuva-Gómez, E., Chasi-Pesántez, P. (2019). Slot-Ultra-Wideband Patch Antenna for Wireless Body Area Networks Applications. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2018. Advances in Intelligent Systems and Computing, vol 787. Springer, Cham. https://doi.org/10.1007/978-3-319-94229-2_8
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DOI: https://doi.org/10.1007/978-3-319-94229-2_8
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