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ObjectiveAccurate estimation of food portion size is of paramount importance in dietary studies. We have developed a small, chest-worn electronic device called eButton which automatically takes pictures of consumed foods for objective dietary assessment. From the acquired pictures, the food portion size can be calculated semi-automatically with the help of computer software. The aim of the present study is to evaluate the accuracy of the calculated food portion size (volumes) from eButton pictures.DesignParticipants wore an eButton during their lunch. The volume of food in each eButton picture was calculated using software. For comparison, three raters estimated the food volume by viewing the same picture. The actual volume was determined by physical measurement using seed displacement.SettingDining room and offices in a research laboratory.SubjectsSeven lab member volunteers.ResultsImages of 100 food samples (fifty Western and fifty Asian foods) were collected and each food volume was estimated from these images using software. The mean relative error between the estimated volume and the actual volume over all the samples was −2·8 % (95 % CI −6·8 %, 1·2 %) with sd of 20·4 %. For eighty-five samples, the food volumes determined by computer differed by no more than 30 % from the results of actual physical measurements. When the volume estimates by the computer and raters were compared, the computer estimates showed much less bias and variability.ConclusionsFrom the same eButton pictures, the computer-based method provides more objective and accurate estimates of food volume than the visual estimation method. [ABSTRACT FROM AUTHOR]

Recent advances in mobile devices have made profound changes in people's daily lives. In particular, the impact of easy access of information by the smartphone has been tremendous. However, the impact of mobile devices on healthcare has been limited. Diagnosis and treatment of diseases are still initiated by occurrences of symptoms, and technologies and devices that emphasize on disease prevention and early detection outside hospitals are under-developed. Besides healthcare, mobile devices have not yet been designed to fully benefit people with special needs, such as the elderly and those suffering from certain disabilities, such blindness. In this paper, an overview of our research on a new wearable computer called eButton is presented. The concepts of its design and electronic implementation are described. Several applications of the eButton are described, including evaluating diet and physical activity, studying sedentary behavior, assisting the blind and visually impaired people, and monitoring older adults suffering from dementia.

Eating event detection is an important problem in automatic dietary study using a wearable computer, such as the eButton. In this work, we approach this detection problem based on the use of a small magnet marker attached to a finger and a miniature magnetometer installed within the eButton. Our experimental results indicate that our magnetic approach is effective when the distance between the marker and the wearable computer is within 12cm, and the range of detection is approximately 15cm. We also found that the proximity signal patterns corresponding to eating and other daily activities are different, which can be used to reduce the false detection rate. In addition, our approach is convenient, low-cost and energy efficient, suitable for practical applications.

A wearable computer, called eButton, has been developed for evaluation of the human lifestyle. This ARM-based device acquires multimodal data from a camera module, a motion sensor, an orientation sensor, a light sensor and a GPS receiver. Its performance has been tested both in our laboratory and by human subjects in free-living conditions. Our results indicate that eButton can record real-world data reliably, providing a powerful tool for the evaluation of lifestyle for a broad range of applications.

A recent study on witricity (wireless electricity) has demonstrated that wireless energy can be delivered over a moderate distance using strongly coupled magnetic resonance. The objective of this work is to apply the witricity technology to the problem of powering a wireless Body Sensor Network (wBSN). The theory of witricity is investigated using coupled mode theory. Compact witricity resonators are designed, and a working prototype of witricity powered wBSN is built and evaluated. An energy transfer efficiency of about 80 % over a distance of 15 cm is achieved. Besides the high efficiency, it has been observed that a certain misalignment between the transmitter and receiver has little effect on the power transfer. Our experimental results indicate that witricity provides a powerful solution to the energy supply problem of wBSN.