Enhancing Food Intake Tracking in Long-term Care With Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology: Validation and Feasibility Assessment

@article{Pfisterer2021EnhancingFI,
  title={Enhancing Food Intake Tracking in Long-term Care With Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology: Validation and Feasibility Assessment},
  author={Kaylen J. Pfisterer and Robert Amelard and Jennifer Boger and Audrey G. Chung and Heather H. Keller and Alexander Wong},
  journal={JMIR Aging},
  year={2021},
  volume={5}
}
Background Half of long-term care (LTC) residents are malnourished, leading to increased hospitalization, mortality, and morbidity, with low quality of life. Current tracking methods are subjective and time-consuming. Objective This paper presented the automated food imaging and nutrient intake tracking technology designed for LTC. Methods A needs assessment was conducted with 21 participating staff across 12 LTC and retirement homes. We created 2 simulated LTC intake data sets comprising… 
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SHOWING 1-10 OF 102 REFERENCES

Automated food intake tracking requires depth-refined semantic segmentation to rectify visual-volume discordance in long-term care homes

This system provides improved transparency, approximates human assessors with enhanced objectivity, accuracy, and precision while avoiding hefty semi-automatic method time requirements, and may help address short-comings currently limiting utility of automated early malnutrition detection in resource-constrained LTC and hospital settings.

Validation of a novel image-weighed technique for monitoring food intake and estimation of portion size in hospital settings: a pilot study

Considering the huge benefits associated with routine monitoring, technological advances have made it possible to develop a novel, easy-to-use DIMS that, according to the findings, is a valid alternative for use in hospital settings.

Prototyping the Automated Food Imaging and Nutrient Intake Tracking System: Modified Participatory Iterative Design Sprint

The AFINI-T concept system appears to have good practice relevance as a tool for an intelligent food and fluid intake tracking system in LTC and gives tangible examples of how the sprint method can be adapted and applied to the development of novel needs-based application-driven technology.

Volume estimation using food specific shape templates in mobile image-based dietary assessment

The objective of this study is to automatically estimate food volumes through the use of food specific shape templates, providing a consistent method for estimation food volume.

Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone: Preclinical Study

Although estimation accuracy was not affected by the viewing angle, the type of meal mattered, with slightly worse performance for cooked meals than for breakfasts and snacks, highlighting its usability.

Recognition and volume estimation of food intake using a mobile device

This paper combines several vision techniques (visual recognition and 3D reconstruction) to achieve quantitative food intake estimation and presents a system that improves accuracy of food intake assessment using computer vision techniques.

Model-based food volume estimation using 3D pose

A novel food portion size estimation method for rigid food items using a single image and the experimental results of this method validate the accuracy and reliability of the model-based approach.

Image-Based Food Classification and Volume Estimation for Dietary Assessment: A Review

After a comprehensive exploration, it is found that integrated dietary assessment systems combining with different approaches could be the potential solution to tackling the challenges in accurate dietary intake assessment.

Modified Texture Food Use is Associated with Malnutrition in Long Term Care: An Analysis of Making the Most of Mealtimes (M3) Project

Prescription of minced or pureed foods was significantly associated with the risk of malnutrition among residents living in LTC facilities while adjusting for other covariates.

Dietary intake assessment using integrated sensors and software

The DDRS consists of a mobile device that integrates a smartphone and an integrated laser package, an algorithm to process acquired data for food volume estimation, which is the largest source of error in calculating dietary intake, and database and interface for data storage and management.
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