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. 2011 Oct;65(10):1156-62.
doi: 10.1038/ejcn.2011.75. Epub 2011 May 18.

Feasibility testing of an automated image-capture method to aid dietary recall

L Arab  1 , D Estrin, D H Kim, J Burke, J Goldman
Affiliations

Feasibility testing of an automated image-capture method to aid dietary recall

L Arab et al. Eur J Clin Nutr. 2011 Oct.

Abstract

Background/objectives: The accuracy of dietary recalls might be enhanced by providing participants with photo images of foods they consumed during the test period.

Subjects/methods: We examined the feasibility of a system (Image-Diet Day) that is a user-initiated camera-equipped mobile phone that is programmed to automatically capture and transmit images to a secure website in conjunction with computer-assisted, multipass, 24-h dietary recalls in 14 participants during 2007. Participants used the device during eating periods on each of the three independent days. Image processing filters successfully eliminated underexposed, overexposed and blurry images. The captured images were accessed by the participants using the ImageViewer software while completing the 24-h dietary recall on the following day.

Results: None of the participants reported difficulty using the ImageViewer. Images were deemed 'helpful' or 'sort of helpful' by 93% of participants. A majority (79%) of users reported having no technical problems, but 71% rated the burden of wearing the device as somewhat to very difficult, owing to issues such as limited battery life, self-consciousness about wearing the device in public and concerns about the field of view of the camera.

Conclusion: Overall, these findings suggest that automated imaging is a promising technology to facilitate dietary recall. The challenge of managing the thousands of images generated can be met. Smaller devices with a broader field of view may aid in overcoming self-consciousness of the user with using or wearing the device.

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Conflict of interest statement

CONFLICT OF INTEREST

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1. Overview of System Components, Processes and Data Flow
The flow of image information in Image-DietDay comprises the following steps: 1) capture; 2) upload to the SensorBase Server; 3) storage in the data repository; 4) processing; 5) sequential clustering; 6) display on the Centrax web server; 7) deletion of user-identified private images, sharing of user-identified public images, and use of images by volunteers to complete 24-hour recalls; 8) compliance tracking by SensorBase, including frequency of uploading. An automated reminder system (9) prompts users to complete required actions.
Figure 2
Figure 2. Image of the Mobile Phone
An image of participant wearing camera-embedded used in study.
Figure 3
Figure 3. Schematic of Image Processing in Image DietDay
A) Schematic of image filtering and clustering, with removal of unusable or private images. B) Key images representing each cluster; C) Expanded views of all related images within a cluster.
Figure 4
Figure 4. Example of Presentation of Food Images for Subject Review
A web-based ImageViewer was used by participants to access images after filtering; participants could then delete images deemed private from the public record.
See this image and copyright information in PMC

Comment in

References

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