Comparing metabolic energy expenditure estimation using wearable multi-sensor network and single accelerometer

Annu Int Conf IEEE Eng Med Biol Soc. 2013:2013:2866-9. doi: 10.1109/EMBC.2013.6610138.

Abstract

This paper presents the implementation details, system architecture and performance of a wearable sensor network that was designed for human activity recognition and energy expenditure estimation. We also included ActiGraph GT3X+ as a popular single sensor solution for detailed comparison with the proposed wearable sensor network. Linear regression and Artificial Neural Network are implemented and tested. Through a rigorous system study and experiment, it is shown that the wearable multi-sensor network outperforms the single sensor solution in terms of energy expenditure estimation.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Acceleration
  • Adult
  • Energy Metabolism*
  • Equipment Design
  • Female
  • Humans
  • Linear Models
  • Male
  • Monitoring, Ambulatory / instrumentation*
  • Monitoring, Ambulatory / methods
  • Neural Networks, Computer*
  • Regression Analysis
  • Signal Processing, Computer-Assisted
  • Telemetry / instrumentation*
  • Young Adult