Enhancing Food Intake Tracking in Long-Term Care with Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology

@article{Pfisterer2022EnhancingFI,
  title={Enhancing Food Intake Tracking in Long-Term Care with Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology},
  author={Kaylen J. Pfisterer and Robert Amelard and Jennifer Boger and Audrey G. Chung and Heather H. Keller and Alexander Wong},
  journal={ArXiv},
  year={2022},
  volume={abs/2112.04608}
}
Half of long-term care (LTC) residents are malnourished increasing hospitalization, mortality, morbidity, with lower quality of life. Current tracking methods are subjective and time consuming. This paper presents the automated food imaging and nutrient intake tracking (AFINI-T) technology designed for LTC. We propose a novel convolutional autoencoder for food classification, trained on an augmented UNIMIB2016 dataset and tested on our simulated LTC food intake dataset (12 meal scenarios; up to… 

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References

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