title: Image-assisted dietary assessment: a systematic review of the evidence.
abstract: Images captured during eating episodes provide objective information to assist in the assessment of dietary intake. Images are captured using handheld devices or wearable cameras, and can support traditional self-report or provide the primary record of dietary intake. A diverse range of image-assisted methods have been developed and evaluated but have not been previously examined together. Therefore, a review was undertaken to examine all studies that have evaluated or validated image-assisted methods of dietary assessment for assessing dietary energy intake. Identified image-assisted methods that employ similar methodologies were grouped for comparison. English-language full-text research articles published between January 1998 and November 2013 were searched using five electronic databases. A search of reference lists and associated websites was also conducted. Thirteen studies that evaluated 10 unique image-assisted methods among adults aged 18 to 70 years were included. Ten studies used handheld devices and three studies used wearable cameras. Eight studies evaluated image-based food records, two studies explored the use of images to enhance written food records, and three studies evaluated image-assisted 24-hour dietary recalls. Results indicate images enhance self-report by revealing unreported foods and identify misreporting errors not captured by traditional methods alone. Moreover, when used as the primary record of dietary intake, images can provide valid estimates of energy intake. However, image-assisted methods that rely on image analysis can be prone to underestimation if users do not capture images of satisfactory quality before all foods are consumed. Further validation studies using criterion measures are warranted. The validity among children, adolescents, and elderly persons as well as the feasibility of using image-assisted methods in large samples needs to be examined. Additional research is also needed to better understand the potential applications and pitfalls of wearable cameras.
authors.forename: Luke
authors.initials: L
authors.lastname: Gemming
authors.forename: Jennifer
authors.initials: J
authors.lastname: Utter
authors.forename: Cliona
authors.initials: C
authors.lastname: Ni Mhurchu
mesh_terms: D016208:Databases, Factual; D015930:Diet Records; D002149:Energy Intake; D005247:Feeding Behavior; D006801:Humans; D007091:Image Processing, Computer-Assisted; D011939:Mental Recall; D015596:Nutrition Assessment; D015203:Reproducibility of Results; D012107:Research Design
keywords: Dietary assessment; Handheld computers; Image analysis; Nutrition assessment; Wearable cameras