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

ABSTRACT:

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 modified (664/1039, 63.91% plates) and regular (375/1039, 36.09% plates) texture foods. Overhead red-green-blue-depth images of plated foods were acquired, and foods were segmented using a pretrained food segmentation network. We trained a novel convolutional autoencoder food feature

SUBMITTER: Pfisterer K 

PROVIDER: S-EPMC9716425 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature