Objective:  The objective of this paper is to describe and evaluate an algorithm to reduce power usage and increase battery lifetime for wearable health-monitoring devices.  Methods:  We describe a novel dynamic computation offloading scheme for real-time wearable health monitoring devices that adjusts the partitioning of data processing between the wearable device and mobile application as a function of desired classification accuracy.  Results:  By making the correct offloading decision based on current system parameters, we show that we are able to reduce system power by as much as 20%.  Conclusion:  We demonstrate that computation offloading can be applied to real-time monitoring systems, and yields significant power savings.  Significance:  Making correct offloading decisions for health monitoring devices can extend battery life and improve adherence.
['Haik Kalantarian', 'Costas Sideris', 'Bobak Mortazavi', 'Nabil Alshurafa', 'Majid Sarrafzadeh']
Dynamic Computation Offloading for Low-Power Wearable Health Monitoring Systems