• DocumentCode
    3715871
  • Title

    Opportunities and challenges for ultra low power signal processing in wearable healthcare

  • Author

    Alexander J. Casson

  • Author_Institution
    School of Electrical and Electronic Engineering, The University of Manchester, UK
  • fYear
    2015
  • Firstpage
    424
  • Lastpage
    428
  • Abstract
    Wearable devices are starting to revolutionise healthcare by allowing the unobtrusive and long term monitoring of a range of body parameters. Embedding more advanced signal processing algorithms into the wearable itself can: reduce system power consumption; increase device functionality; and enable closed-loop recording-stimulation with minimal latency; amongst other benefits. The design challenge is in realising algorithms within the very limited power budgets available. Wearable algorithms are now emerging to answer this challenge. Using a new review, and examples from a case study on EEG analysis, this article overviews the state-of-the-art in wearable algorithms. It demonstrates the opportunities and challenges, highlighting the open challenge of performance assessment and measuring variability.
  • Keywords
    "Signal processing algorithms","Algorithm design and analysis","Signal processing","Electrocardiography","Biomedical monitoring","Power demand","Electroencephalography"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2015 23rd European
  • Electronic_ISBN
    2076-1465
  • Type

    conf

  • DOI
    10.1109/EUSIPCO.2015.7362418
  • Filename
    7362418