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Paper wins BEST PAPER AWARD at Bodynets 2013

The paper titled "Energy Expenditure Estimation with Smartphone Body Sensors" wins Best Paper Award in 8th International Conference on Body Area Networks (ICST Bodynets 2013) to be held in Boston on September 30- October 2, 2013.

The paper titled "Energy Expenditure Estimation with Smartphone Body Sensors" has been accepted for presentation in 8th International Conference on Body Area Networks (ICST Bodynets 2013) to be held in Boston on September 30- October 2, 2013. In this work, we focus on accurate EEE for tracking ambulatory activities (walking, standing, climbing upstairs or downstairs) of a common smartphone user. We used existing smartphone sensors (accelerometer and barometer sensor), sampled at low frequency, to accurately detect EEE. We used Artificial Neural Networks, a machine learning technique to build a generic regression model for EEE that yields upto 89%correlation with actual Energy Expenditure (EE). Accurate and online Energy Expenditure Estimation utilizing small wearable sensors is a difficult task, primarily because most existing schemes work offline or using heuristics. In this work, we focus on accurate Energy Expenditure Estimation for tracking ambulatory activities (walking, standing, climbing upstairs or downstairs) of a common smartphone user. We used existing smartphone sensors (accelerometer and barometer sensor), sampled at low frequency, to accurately detect Energy Expenditure Estimation. Using Artificial Neural Networks, a machine learning technique, we build a generic regression model for Energy Expenditure Estimation that yields upto 89% correlation with actual Energy Expenditure (EE). Using barometer data, in addition to accelerometry is found to significantly improve Energy Expenditure Estimation performance (upto 15%). We compare our results against stateof- the-art Calorimetry Equations (CE) and consumer electronics devices (Fitbit and Nike+ Fuel Band). We were able to demonstrate the superior accuracy achieved by our algorithm. The results were calibrated against COSMED K4b2 calorimeter readings.

The full announcement can be found here.

The preliminary poster version of this paper appears in ACM Wireless Health 2013.

 

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