Published on in Vol 5, No 4 (2022): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37590, first published .
Enhancing Food Intake Tracking in Long-term Care With Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology: Validation and Feasibility Assessment

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

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

Kaylen Pfisterer   1, 2, 3, 4 * , BSc, MSc, PhD ;   Robert Amelard   3, 5 * , BSE, MASc, PhD ;   Jennifer Boger   1, 3, 5 , BSc, MASc, PhD ;   Heather Keller   3, 6 , BASc, MSc, PhD ;   Audrey Chung   1, 2 , BASc, MASc, PhD ;   Alexander Wong   1, 2, 3 , BASc, MASc, PhD

1 Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada

2 Waterloo AI Institute, Waterloo, ON, Canada

3 Schlegel-University of Waterloo Institute for Aging, Waterloo, ON, Canada

4 Centre for Digital Therapeutics, Techna Institute, University Health Network, Toronto, ON, Canada

5 KITE-Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada

6 Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada

*these authors contributed equally

Corresponding Author:

  • Kaylen Pfisterer, BSc, MSc, PhD
  • Department of Systems Design Engineering
  • University of Waterloo
  • 200 University Ave W
  • Waterloo, ON, N2L 3G1
  • Canada
  • Phone: 1 519 888 4567
  • Email: kaylen.pfisterer@uhn.ca