Corpus ID: 204852024

Fully-Automatic Semantic Segmentation for Food Intake Tracking in Long-Term Care Homes

@article{Pfisterer2019FullyAutomaticSS,
  title={Fully-Automatic Semantic Segmentation for Food Intake Tracking in Long-Term Care Homes},
  author={Kaylen J. Pfisterer and Robert Amelard and Audrey G. Chung and Braeden Syrnyk and Alexander MacLean and Alexander Wong},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.11250}
}
Malnutrition impacts quality of life and places annually-recurring burden on the health care system. Half of older adults are at risk for malnutrition in long-term care (LTC). Monitoring and measuring nutritional intake is paramount yet involves time-consuming and subjective visual assessment, limiting current methods' reliability. The opportunity for automatic image-based estimation exists. Some progress outside LTC has been made (e.g., calories consumed, food classification), however, these… Expand
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