title: Dynamic Computation Offloading for Low-Power Wearable Health Monitoring Systems.
abstract: 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.
  
  
  
  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.
  
  
  
  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%.
  
  
  
  We demonstrate that computation offloading can be applied to real-time monitoring systems, and yields significant power savings.
  
  
  
  Making correct offloading decisions for health monitoring devices can extend battery life and improve adherence.
authors.forename: Haik
authors.initials: H
authors.lastname: Kalantarian
authors.forename: Costas
authors.initials: C
authors.lastname: Sideris
authors.forename: Bobak
authors.initials: B
authors.lastname: Mortazavi
authors.forename: Nabil
authors.initials: N
authors.lastname: Alshurafa
authors.forename: Majid
authors.initials: M
authors.lastname: Sarrafzadeh
mesh_terms: D000465:Algorithms; D011211:Electric Power Supplies; D004867:Equipment Design; D019544:Equipment Failure Analysis; D016247:Information Storage and Retrieval / Q000379:methods*; D063731:Mobile Applications; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D000068997:Smartphone / Q000295:instrumentation*; D017216:Telemedicine / Q000295:instrumentation / Q000379:methods; D059015:Wireless Technology / Q000295:instrumentation