Trading off power consumption and prediction performance in wearable motion sensors: An optimal and real-time approach

Ramin Fallahzadeh, Hassan Ghasemzadeh

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Power consumption is identified as one of the main complications in designing practical wearable systems, mainly due to their stringent resource limitations. When designing wearable technologies, several system-level design choices, which directly contribute to the energy consumption of these systems, must be considered. In this article, we propose a computationally lightweight system optimization framework that trades off power consumption and performance in connected wearable motion sensors. While existing approaches exclusively focus on one or a few hand-picked design variables, our framework holistically finds the optimal power-performance solution with respect to the specified application need. Our design tackles a multi-variant non-convex optimization problem that is theoretically hard to solve. To decrease the complexity, we propose a smoothing function that reduces this optimization to a convex problem. The reduced optimization is then solved in linear time using a devised derivative-free optimization approach, namely cyclic coordinate search. We evaluate our framework against several holistic optimization baselines using a real-world wearable activity recognition dataset. We minimize the energy consumption for various activity-recognition performance thresholds ranging from 40% to 80% and demonstrate up to 64% energy savings.

Original languageEnglish (US)
Article number67
JournalACM Transactions on Design Automation of Electronic Systems
Issue number5
StatePublished - Oct 2018
Externally publishedYes


  • Activity recognition
  • Body sensor networks
  • Embedded systems
  • Energy optimization
  • Wearable monitoring systems

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering


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