Preferred Name
Jason Fee
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Date of Graduation
12-16-2022
Semester of Graduation
Fall
Degree Name
Master of Science (MS)
Department
Department of Kinesiology
Abstract
Technology has played a key role in advancing the health and agriculture sectors to improve obesity rates, diseasecontrol, food waste, and overall health disparities. However, these health and lifestyle determinants continue to plague theUnited States population. While new technologies have been and are currently being developed to address these concerns, they may not be practical for the general population. Utilizing machine learning advancement in food recognition using smartphone technology may be a means to improve the dietary component of nutrition assessments while providing valuable nutrition feedback. This narrative review was conducted to assess the current state of the literature on nutrition technology using image recognition for practical applications, while also proposing theoretical uses for the technology to improve quality of life through dietary feedback.
