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

Authors :
Mohammad Saeedi
Ali Maddahi
Amir Mahdi Nassiri
Michael Jackson
Kourosh Zareinia
Source :
Applied Sciences, Vol 12, Iss 10, p 4966 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

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.

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.b4cfbcd9fe2c467bafc1b6603223b844
Document Type :
article
Full Text :
https://doi.org/10.3390/app12104966