Energy harvesting modelling for self-powered fitness gadgets: a feasibility study

Abstract

The idea of employing scavenged energy from human motion to run electronic devices is attracting increased attention of many researchers worldwide. However, there is still limited knowledge of energy characteristics generated by human motions. Moreover, level of human activities varies during a day from sitting for several hours to running on a treadmill. This highlights a vital need for energy harvesting modelling. Hence, in this paper, we aim to investigate the feasibility of running a simple fitness gadget with scavenged energy from human motions. We analyse kinetic energy generated by human activities and develop energy harvesting modelling techniques which estimate the required time for a device to store needed energy between each active periods. Two large, real-world data sets are employed to obtain empirical results for different motion scenarios. We believe these results are informative to the design of energy harvesting fitness gadgets with sensing applications.