Dynamic Computation Offloading for Low-Power Wearable Health Monitoring Systems

作者：Kalantarian Haik^*; Sideris Costas; Mortazavi Bobak; Alshurafa Nabil; Sarrafzadeh Majid

来源：IEEE Transactions on Biomedical Engineering, 2017, 64(3): 621-628.

DOI：10.1109/TBME.2016.2570210

• Machine learning
• pervasive computing
• power optimization
• signal processing

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.

• 出版日期2017-3
• 单位西北大学