Machine Learning and Sensor Fusion for Estimating Continuous Energy Expenditure

Authors

  • Nisarg Vyas BodyMedia, Inc.
  • Jonathan Farringdon BodyMedia Inc.
  • David Andre Cerebellum Capital, Inc.
  • John Ivo Stivoric BodyMedia

DOI:

https://doi.org/10.1609/aimag.v33i2.2408

Abstract

In this article we provide insight into the BodyMedia FIT armband system — a wearable multi-sensor technology that continuously monitors physiological events related to energy expenditure for weight management using machine learning and data modeling methods. Since becoming commercially available in 2001, more than half a million users have used the system to track their physiological parameters and to achieve their individual health goals including weight-loss. We describe several challenges that arise in applying machine learning techniques to the health care domain and present various solutions utilized in the armband system. We demonstrate how machine learning and multi-sensor data fusion techniques are critical to the system’s success.

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Published

2012-03-16

How to Cite

Vyas, N., Farringdon, J., Andre, D., & Stivoric, J. I. (2012). Machine Learning and Sensor Fusion for Estimating Continuous Energy Expenditure. AI Magazine, 33(2), 55. https://doi.org/10.1609/aimag.v33i2.2408

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Section

Articles