CageView: A Smart Food Control and Monitoring System for Phenotypical Research In Vivo

Abstract

The present work introduces an automated and smart system (named CageView) used to monitor a mouse, detect motion, and control access to food in accordance with experimental schedules. We describe the components of the CageView platform and give a summarized description on how we employed a convolutional neural network to detect and recognize a mouse in real time before presenting the results of a case study. In particular, CageView is a programmable and remotely operable system such that (1) an experimenter at a remote workstation may set up a feeding and fasting schedule that allows feeding and fasting without requiring the physical presence of a staff member, (2) the experimenter can control access to food in real time regardless of the preset schedule, (3) the experimenter has real-time access to a live video feed to assess the mouse, (4) an artificial intelligence system tracks the mouse’s location and physical activity, and (5) a record is kept of activity, which can be displayed as a 2D representation of mouse movement or a histogram showing mouse movement in 15-min blocks for the duration of the experiment.

Keywords

• biomedical research
• mouse
• rodent
• intermittent fasting
• activity monitoring