Title :
Statistical Models for Harvested Power From Human Motion
Author :
Shenqiu Zhang ; Seyedi, Alireza
Author_Institution :
Qualcomm, San Diego, CA, USA
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;
Journal_Title :
Selected Areas in Communications, IEEE Journal on
DOI :
10.1109/JSAC.2015.2391871