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• Conference paper
  Nilforooshan R, Rostill H, Barnaghi P, Enshaeifar S, Markides A, Skillman S, Kenny Met al., 2019,

  Transforming care for people with dementia using the Internet of Things

  , Publisher: UBIQUITY PRESS LTD, ISSN: 1568-4156
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  • Citations: 3
• Conference paper
  De Marcellis A, Di Patrizio Stanchieri G, Palange E, Faccio M, Constandinou TGet al., 2018,

  An ultra-wideband-inspired system-on-chip for an optical bidirectional transcutaneous biotelemetry

  , IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 351-354

  This paper describes an integrated communicationsystem, implementing a UWB-inspired pulsed coding technique,for an optical transcutaneous biotelemetry. The system consistsof both a transmitter and a receiver facilitating a bidirectionallink. The transmitter includes a digital data coding circuit and iscapable of generating sub-nanosecond current pulses and directlydriving an off-chip semiconductor laser diode including all biasand drive circuits. The receiver includes an integrated compactPN-junction photodiode together with signal conditioning, de-tection and digital data decoding circuits to enable a high bitrate, energy efficient communication. The proposed solution hasbeen implemented in a commercially available 0.35μm CMOStechnology provided by AMS. The circuit core occupies a compactsilicon footprint of less than 0.13 mm2(only 113 transistors and1 resistor). Post-layout simulations have validated the overallsystem operation demonstrating the ability to operate at bit ratesup to 500 Mbps with pulse widths of 300 ps with a total powerefficiency (transmitter + receiver) lower than 74 pJ/bit. Thismakes the system ideally suited for demanding applications thatrequire high bit rates at extremely low energy levels. One suchapplication is implantable brain machine interfaces requiringhigh uplink bitrates to transmit recorded data externally througha transcutaneous communication channel.

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• Journal article
  Li H, Enshaeifar S, Skillman S, Markides A, Kenny M, Sharp D, Rostill H, Nilforooshan R, Barnaghi Pet al.,

  A Semi-Supervised Machine Learning Model for Risk Analysis of Urinary Tract Infections in People with Dementia

  • Cite

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