Energy-Optimal Gesture Recognition using Self-Powered Wearable Devices

Jaehyun Park, Ganapati Bhat, Cemil S. Geyik, Hyung Gyu Lee, Umit Ogras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Small form factor and low-cost wearable devices enable a variety of applications including gesture recognition, health monitoring, and activity tracking. Energy harvesting and optimal energy management are critical for the adoption of these devices, since they are severely constrained by battery capacity. This paper considers optimal gesture recognition using self-powered devices. We propose an approach to maximize the number of gestures that can be recognized under energy budget and accuracy constraints. We construct a computationally efficient optimization algorithm with the help of analytical models derived using the energy consumption breakdown of a wearable device. Our empirical evaluations demonstrate up to 2.4 x increase in the number of recognized gestures compared to a manually optimized solution.

Original languageEnglish (US)
Title of host publication2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538636039
DOIs
StatePublished - Dec 20 2018
Event2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Cleveland, United States
Duration: Oct 17 2018Oct 19 2018

Other

Other2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018
CountryUnited States
CityCleveland
Period10/17/1810/19/18

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Health Informatics
  • Instrumentation
  • Signal Processing
  • Biomedical Engineering

Fingerprint Dive into the research topics of 'Energy-Optimal Gesture Recognition using Self-Powered Wearable Devices'. Together they form a unique fingerprint.

  • Cite this

    Park, J., Bhat, G., Geyik, C. S., Lee, H. G., & Ogras, U. (2018). Energy-Optimal Gesture Recognition using Self-Powered Wearable Devices. In 2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Proceedings [8584746] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIOCAS.2018.8584746