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Food Composition Impacts the Accuracy of Wearable Devices When Estimating Energy Intake from Energy-Dense Food

Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35131 Padova, Italy
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Received: 1 April 2019 / Revised: 20 May 2019 / Accepted: 21 May 2019 / Published: 24 May 2019
The present study aimed to assess the feasibility and reliability of an a3utomatic food intake measurement device in estimating energy intake from energy-dense foods. Eighteen volunteers aged 20–36 years were recruited from the University of Padova. The device used in the present study was the Bite Counter (Bite Technologies, Pendleton, USA). The rationale of the device is that the wrist movements occurring in the act of bringing food to the mouth present unique patterns that are recognized and recorded by the Bite Counter. Subjects were asked to wear the Bite Counter on the wrist of the dominant hand, to turn the device on before the first bite and to turn it off once he or she finished his or her meal. The accuracy of caloric intake was significantly different among the methods used. In addition, the device’s accuracy in estimating energy intake varied according to the type and amount of macronutrients present, and the difference was independent of the number of bites recorded. Further research is needed to overcome the current limitations of wearable devices in estimating caloric intake, which is not independent of the food being eaten. View Full-Text
Keywords: energy intake; energy-dense food; automatic food intake measurement energy intake; energy-dense food; automatic food intake measurement
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MDPI and ACS Style

Lorenzoni, G.; Bottigliengo, D.; Azzolina, D.; Gregori, D. Food Composition Impacts the Accuracy of Wearable Devices When Estimating Energy Intake from Energy-Dense Food. Nutrients 2019, 11, 1170. https://0-doi-org.brum.beds.ac.uk/10.3390/nu11051170

AMA Style

Lorenzoni G, Bottigliengo D, Azzolina D, Gregori D. Food Composition Impacts the Accuracy of Wearable Devices When Estimating Energy Intake from Energy-Dense Food. Nutrients. 2019; 11(5):1170. https://0-doi-org.brum.beds.ac.uk/10.3390/nu11051170

Chicago/Turabian Style

Lorenzoni, Giulia, Daniele Bottigliengo, Danila Azzolina, and Dario Gregori. 2019. "Food Composition Impacts the Accuracy of Wearable Devices When Estimating Energy Intake from Energy-Dense Food" Nutrients 11, no. 5: 1170. https://0-doi-org.brum.beds.ac.uk/10.3390/nu11051170

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