%0 Conference Proceedings %T Modeling and Characterization of in-Body Antennas %+ Universiteit Gent = Ghent University (UGENT) %+ Institut d'Électronique et des Technologies du numéRique (IETR) %A Nikolayev, Denys %Z BodyCap Company %Z French National Center for Scientific Research through the PEPS program %Z DGA through the PEPS program %Z Rennes Metropole through the AES program %< avec comité de lecture %( 17th IEEE International Conference on Mathematical Methods in Electromagnetic Theory (MMET) %B 17th IEEE International Conference on Mathematical Methods in Electromagnetic Theory (MMET) %C Kyiv, Ukraine %I IEEE %8 2018-07-02 %D 2018 %K biomedical telemetry %K implantable %K in-body %K ingestible %K ISM (industrial %K scientific %K and medical) band %K microstrip antennas %K miniature antennas %K phantom %K robust antennas %Z Engineering Sciences [physics]Conference papers %X Emerging wireless in-body devices pave the way to many breakthroughs in healthcare and clinical research. This technology enables monitoring of physiological parameters while maintaining mobility and freedom of movement of its user. However, establishing reliable communication between an in-body device and external equipment is still a major challenge. The radiation efficiency is constrained by attenuation and reflection losses in tissues. Furthermore, the antennas suffer from impedance detuning issues caused by uncertain electromagnetic properties of body tissues. First, we show that choosing an optimal operating frequency depends on application scenarios and can reduce the losses. Specific designs are then discussed to mitigate the antenna detuning effects due to surrounding biological tissue. Modeling approaches are proposed to lessen the design and optimization complexity. Finally, we present an accurate characterization method of in-body antennas in canonical phantoms using analog fiber optic links. %G English %L hal-01900811 %U https://univ-rennes.hal.science/hal-01900811 %~ UNIV-NANTES %~ UNIV-RENNES1 %~ CNRS %~ INSA-RENNES %~ IETR %~ STATS-UR1 %~ CENTRALESUPELEC %~ UR1-HAL %~ UR1-MATH-STIC %~ UR1-UFR-ISTIC %~ TEST-UR-CSS %~ UNIV-RENNES %~ INSA-GROUPE %~ TEST-HALCNRS %~ UR1-MATH-NUM %~ IETR-EWAVES %~ NANTES-UNIVERSITE %~ UNIV-NANTES-AV2022