Real-Time Estimation of Energy Expenditure using Noninvasive Wearable Sensors for Multivariable Artificial Pancreas System

Mert Sevil1, Mudassir Rashid, Zacharie Maloney, Sediqeh Samadi, Caterina Lazaro1, Nicole Frantz, Iman Hajizadeh, Jianyuan Feng, Rachel Brandt, Ali Cinar1

  • 1Illinois Institute of Technology

Details

18:15 - 20:15 | Mon 5 Mar | Caribbean ABC | MoPO.16

Session: Poster Session # 1 and BSN Innovative Health Technology Demonstrations

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Abstract

Accurate estimates of energy expenditure (EE) can quantify the physical activity level and provide useful feedback for mitigating the risk factors of chronic diseases such as diabetes. A real-time EE estimation approach using noninvasive measurements of physiological variables obtained through a wrist-worn activity tracker is proposed. Experiments are con- ducted to collect data for evaluating the proposed real-time EE estimation method under various physical activity levels, and the results are compared to the BodyMedia SenseWear armband.