• DocumentCode
    110964
  • Title

    Corrections to “Predicting Free-Living Energy Expenditure Using a Miniaturized Ear-Worn Sensor: An Evaluation Against Doubly Labeled Water” [Feb 14 566-575]

  • Author

    Bouarfa, Loubna ; Atallah, Louis ; Kwasnicki, Richard Mark ; Pettitt, Claire ; Frost, Gordon ; Yang, Guo-Min

  • Author_Institution
    Hamlyn Centre, Imperial College London, London, U.K.
  • Volume
    61
  • Issue
    11
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    2818
  • Lastpage
    2818
  • Abstract
    In the above paper (ibid., vol. 61, no. 2, pp. 566-575, Feb. 2014), the mean absolute deviation was incorrect in the Abstract. This should have read as follows. 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 as 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 (MAD) 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 272 kcal day. These results demonstrate that laboratory-derived prediction models can be used to predict EE under free-living conditions.
  • Keywords
    Accelerometers; Biomedical measurement; Feature extraction; Wearable sensors;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2014.2359079
  • Filename
    6924845