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- W2016395102 abstract "Accurate estimation of daily total energy expenditure (EE) is a prerequisite for assisted weight management and assessing certain health conditions. The use of wearable sensors for predicting free-living EE is challenged by consistent sensor placement, user compliance, and estimation methods used. This paper examines whether a single ear-worn accelerometer can be used for EE estimation under free-living conditions. An EE prediction model was first derived and validated in a controlled setting using healthy subjects involving different physical activities. Ten different activities were assessed showing a tenfold cross validation error of 0.24. Furthermore, the EE prediction model shows a mean absolute deviation below 1.2 metabolic equivalent of tasks. The same model was applied to a free-living setting with a different population for further validation. The results were compared against those derived from doubly labeled water. In free-living settings, the predicted daily EE has a correlation of 0.74, p = 0.008, and a MAD of 27 kcal/day. These results demonstrate that laboratory-derived prediction models can be used to predict EE under free-living conditions." @default.
- W2016395102 created "2016-06-24" @default.
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- W2016395102 date "2014-02-01" @default.
- W2016395102 modified "2023-10-10" @default.
- W2016395102 title "Predicting Free-Living Energy Expenditure Using a Miniaturized Ear-Worn Sensor: An Evaluation Against Doubly Labeled Water" @default.
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- W2016395102 doi "https://doi.org/10.1109/tbme.2013.2284069" @default.
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