A New Method for Measuring Meal Intake in Humans via Automated Wrist Motion Tracking. Dong, Y., Hoover, A., Scisco, J., & Muth, E. Applied psychophysiology and biofeedback, 37(3):205-215, Springer US, 9, 2012.
A New Method for Measuring Meal Intake in Humans via Automated Wrist Motion Tracking [link]Website  abstract   bibtex   
Measuring the energy intake (kcal) of a person in day-to-day life is difficult. The best laboratory tool achieves 95 % accuracy on average, while tools used in daily living typically achieve 60-80 % accuracy. This paper describes a new method for measuring intake via automated tracking of wrist motion. Our method uses a watch-like device with a micro-electro-mechanical gyroscope to detect and record when an individual has taken a bite of food. Two tests of the accuracy of our device in counting bites found that our method has 94 % sensitivity in a controlled meal setting and 86 % sensitivity in an uncontrolled meal setting, with one false positive per every 5 bites in both settings. Preliminary data from daily living indicates that bites measured by the device are positively related to caloric intake illustrating the potential of the device to monitor energy intake. Future research should seek to further explore the relationship between bites taken and kilocalories consumed to validate the device as an automated measure of energy intake.
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 title = {A New Method for Measuring Meal Intake in Humans via Automated Wrist Motion Tracking},
 type = {article},
 year = {2012},
 identifiers = {[object Object]},
 keywords = {activity,auracle,eating,energy,intake,intake-detection,mems,mhealth,recognition,sensors,wearable,wrist},
 pages = {205-215},
 volume = {37},
 websites = {http://view.ncbi.nlm.nih.gov/pubmed/22488204,http://dx.doi.org/10.1007/s10484-012-9194-1},
 month = {9},
 publisher = {Springer US},
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 abstract = {Measuring the energy intake (kcal) of a person in day-to-day life is difficult. The best laboratory tool achieves 95 % accuracy on average, while tools used in daily living typically achieve 60-80 % accuracy. This paper describes a new method for measuring intake via automated tracking of wrist motion. Our method uses a watch-like device with a micro-electro-mechanical gyroscope to detect and record when an individual has taken a bite of food. Two tests of the accuracy of our device in counting bites found that our method has 94 % sensitivity in a controlled meal setting and 86 % sensitivity in an uncontrolled meal setting, with one false positive per every 5 bites in both settings. Preliminary data from daily living indicates that bites measured by the device are positively related to caloric intake illustrating the potential of the device to monitor energy intake. Future research should seek to further explore the relationship between bites taken and kilocalories consumed to validate the device as an automated measure of energy intake.},
 bibtype = {article},
 author = {Dong, Yujie and Hoover, Adam and Scisco, Jenna and Muth, Eric},
 journal = {Applied psychophysiology and biofeedback},
 number = {3}
}

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