• DocumentCode
    18262
  • Title

    Statistical Models for Harvested Power From Human Motion

  • Author

    Shenqiu Zhang ; Seyedi, Alireza

  • Author_Institution
    Qualcomm, San Diego, CA, USA
  • Volume
    33
  • Issue
    8
  • fYear
    2015
  • fDate
    Aug. 2015
  • Firstpage
    1667
  • Lastpage
    1679
  • Abstract
    This paper investigates the statistical properties of human motion-based harvested power, and provides models for the distribution, auto-correlation and cross-correlation of harvested power at different body locations, namely left wrist, right wrist, left ankle and waist. The models are developed based on empirical acceleration measurements while the subjects perform unscripted daily tasks. The measured accelerations are converted to harvestable power by assuming a velocity-damped resonant harvesting generator. The provided models enable realistic analysis and simulation of wearable communication systems with motion-based energy harvesting.
  • Keywords
    energy harvesting; statistical analysis; harvested power autocorrelation; harvested power cross-correlation; harvested power distribution; human motion-based harvested power; left ankle; left wrist; motion-based energy harvesting; right wrist; statistical models; unscripted daily tasks; velocity-damped resonant harvesting generator; wearable communication systems; Acceleration; Correlation; Data models; Power measurement; Probability density function; Sensors; Wrist; Ambient Energy; Empirical Measurements; Energy harvesting; Human-Motion; Statistical Models,; Wearable Devices; ambient energy; empirical measurements; human-motion; statistical models; wearable devices;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/JSAC.2015.2391871
  • Filename
    7009987