期刊
APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK
卷 37, 期 3, 页码 205-215出版社
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10484-012-9194-1
关键词
Energy intake; Eating; Activity recognition; MEMS sensors
资金
- NCRR NIH HHS [UL1 RR029882] Funding Source: Medline
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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