A Wearable Dual-Mode Repeater Antenna for Implant Communications

Godeneli, Kadircan; Bengi, Uzay; Kati, Omer A.; Dumanlı, Sema

doi:10.1109/tap.2021.3111603

Cited by 10 publications

(2 citation statements)

References 23 publications

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“…The antenna's physical dimensions are significantly smaller than its free space wavelength (≪ λ0/10). Hence, it can be classified as an ESA, as defined in [16]. The MPHD topology was realised on a Rogers RO4350 substrate, of height = 0.25 mm, with a dielectric constant εr = 3.66, and a loss tangent, tan δ = 0.0037 at 1 GHz, 23 C.…”

Section: A Antenna Designmentioning

confidence: 99%

Electrically Small Antenna For RFID-Based Implantable Medical Sensor

Andrew

Mugisha

Rigi

et al. 2023

IEEE J. Radio Freq. Identif.

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We present a sub-GHz, low profile Electrically Small Antenna (ESA), designed for UHF RFID miniaturised battery free Implantable Wireless Medical Devices (IWMDs). The custom ESA is a linearly polarised dipole, and its topology leverages a meanderline structure to miniaturise its form factor. Furthermore, the ESA utilises a receded ground plane to improve its gain performance and achieve resonance, at the desired sub-GHz design frequency of 915 MHz. The ESA's dipole characteristics provide an added benefit of 180° bidirectional RF signal propagation. The ESA's design was optimised to integrate the footprint of a UHF RFID sensor chip (SL900A). By integrating the UHF RFID chip on the ESA, a complete wireless battery free sensory medical device, with an integrated antenna, can be realised. The antenna has a formfactor of 12.75×12.25×0.29 mm3. A prototype of the proposed ESA was fabricated and encapsulated in Polydimethylsiloxane (PDMS). Measurements of the prototyped ESA's input reflection coefficient (S11) and farfield gain values, at 915 MHz, were -26.44 dB and -18.88 dBi, respectively and demonstrated significantly better gain and efficiency performance, when compared to peer reviewed work. The ESA can be used as an antenna for various battery-free subcutaneous implants with a connected sensor (e.g. temperature) or actuator (e.g. neurostimulator).

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Section: A Antenna Designmentioning

confidence: 99%

Electrically Small Antenna For RFID-Based Implantable Medical Sensor

Andrew

Mugisha

Rigi

et al. 2023

IEEE J. Radio Freq. Identif.

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“…The patch antenna as seen in Fig. 6(a) is designed to operate in the 2.4 GHz Industrial, Scientific and Medical (ISM) Band on a 1.91 mm-thick Rogers RT/duroid 6006 (ϵ r = 6.15) substrate [47]. The dimensions of the patch and the offset of the feed from the centre are 25 mm × 10 mm and 10 mm, respectively.…”

Section: B Validationmentioning

confidence: 99%

Machine Learning-Based Matching Medium Design for Implant Communications

Cil

Cadir²,

Kati³

et al. 2022

IEEE Trans. Antennas Propagat.

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Matching media are used in various applications to increase the power transmitted into the human body. The selection of the optimum matching medium permittivity is not a straightforward task, as the optimum value maximizing the transmitted power depends on the thickness of the matching medium and the electromagnetic properties of the target tissue. In this paper, a computationally heavy empirical approach and a machine learning-based approach are utilized for the selection of the matching medium. The empirical approach demonstrates that the matching medium can increase the |S 21 | values up to 8 dB, which is validated with measurements. Next, a machine learning-based tool is proposed to predict the optimum matching medium permittivity for any target tissue and any matching medium thickness. A one-dimensional convolutional neural network followed by a multi-layer perceptron is trained with the simulated average Poynting vector magnitudes for muscle and fat as target tissues. The average Poynting vector magnitude and the dipole length for given system parameters are predicted by the trained artificial neural network. The accuracy is calculated by comparison with the results of the empirical analysis and found to be 1% and 12.3% mean absolute percentage error for dipole length and average Poynting vector magnitude, respectively. The proposed tool decreases the time required to milliseconds.

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