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    Item type:Publication, Access status: without files ,
    A Stent Graft Occlusion Detection : Pressure Sensing Implant Device with Inductive Power and Data Telemetry
    (IEEE, 2018-04-26)
    John, Bibin
    ;
    Spink, Clemens
    ;
    Braunschweig, Markus
    ;
    Ranjan, Rajeev
    ;
    Schröder, Dietmar
    Transjugular intrahepatic portosystemic shunt (TIPS) procedure has been used for the treatment of portal hypertension induced due to liver cirrhosis. A small metallic tube called stent graft is inserted during TIPS for rerouting blood flow in the liver. Common complications after TIPS is partial or complete blockage inside or at either ends of the stent graft. This paper presents the design and fabrication of a smart stent graft containing two pressure sensors for detecting blockages occuring after TIPS. The active implant device with pressure sensor is powered wirelessly and it transmits measured pressure data wirelessly to the external monitoring station using inductive coupling. Ferrite inductor antennas are used for wireless power reception and PCB trace antenna is used for wireless data transmission in the implant device. A smart stent graft is fabricated by coating PTFE membrane on the bare stent followed by mounting of the implant devices. The in vivo setup is emulated by placing the smart stent graft inside meat and powering the implant device with wireless inductive telemetry link. Test result shows that implant device can be operated for a wireless range of 4.5 cm using 15 W 2.05 MHz RF power sender.
    Publicationtype: Conference Paper
      177
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    Integration of Double Barrier Memristor Die with Neuron ASIC for Neuromorphic Hardware Learning
    (IEEE, 2018-04-26)
    Ranjan, Rajeev
    ;
    Hansen, Mirko
    ;
    Mendoza Ponce, Pablo Daniel
    ;
    Abu Saleh, Lait
    ;
    Schröder, Dietmar
    This paper details the design of an integrate fire (I F) neuron ASIC and its integration with a double barrier memristor device. The memristor has a non-volatile analog memory characteristic which changes with time and voltage. The neuron ASIC is designed to interact with the memristor by integrating its current and firing when a certain threshold is reached. The resulting spikes increase the memristor's conductance and consequently the firing rate of neuron increases. Together, the ASIC and the memristor mimics neuromorphic learning on hardware. The ASIC has been fabricated in AMS 350nm process.
    Publicationtype: Conference Paper
      186