Dynamic Computation Offloading for Low-Power Wearable Health Monitoring Systems. Academic Article

abstract

• 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.

authors

• Mortazavi, Bobak

published proceedings

• IEEE Trans Biomed Eng

author list (cited authors)

• Kalantarian, H., Sideris, C., Mortazavi, B., Alshurafa, N., & Sarrafzadeh, M.

citation count

• 40

complete list of authors

• Kalantarian, Haik||Sideris, Costas||Mortazavi, Bobak||Alshurafa, Nabil||Sarrafzadeh, Majid

publication date

• March 2017

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Biomedical Engineering  Journal

keywords

• Algorithms
• Electric Power Supplies
• Equipment Design
• Equipment Failure Analysis
• Information Storage And Retrieval
• Mobile Applications
• Monitoring, Ambulatory
• Smartphone
• Telemedicine
• Wireless Technology

PubMed Central ID

• 28113209

Digital Object Identifier (DOI)

• 10.1109/TBME.2016.2570210

start page

• 621

end page

• 628

volume

• 64

issue

• 3

URL

• http://dx.doi.org/10.1109/tbme.2016.2570210