Automated Behavior and Zone Tracking in Laboratory Mice Using CiRA CORE
Automated Behavior and Zone Tracking in Laboratory Mice Using CiRA CORE |
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| © 2025 by IJETT Journal | ||
| Volume-73 Issue-11 |
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| Year of Publication : 2025 | ||
| Author : Thanan Rueankhong, Surachat Chantarachit, Warawut Suwalai, Pharan Chawaphan, Padma Nyoman Crisnapati | ||
| DOI : 10.14445/22315381/IJETT-V73I11P107 | ||
How to Cite?
Thanan Rueankhong, Surachat Chantarachit, Warawut Suwalai, Pharan Chawaphan, Padma Nyoman Crisnapati,"Automated Behavior and Zone Tracking in Laboratory Mice Using CiRA CORE", International Journal of Engineering Trends and Technology, vol. 73, no. 11, pp.79-86, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I11P107
Abstract
This work aims to develop an artificial intelligence-based system to automate the detection and analysis of experimental animal behaviors, thereby reducing reliance on human observation and enhancing consistency in behavioral research. A deep learning model was trained to track motions across five predetermined spatial zones and identify two behaviors (standing and walking) using the CIRA CORE platform, connected to TensorFlow and YOLOv4-tiny. Training and evaluation of the model across datasets of different sizes made use of annotated image frames taken from laboratory video records. When compared to human observers, the system attained detection confidence scores ranging from 54% to 96% for walking and from 50% to 91% for standing, with equivalent behavioural detection accuracy of 86.8% for walking and 89.5% for standing. Using the greatest dataset helped zone transition errors drop to less than 1%. The clarity of the image and the detection performance are clearly linked. These results show the efficiency of the model in real-time behavioural classification and spatial tracking, therefore surpassing conventional human observation in dependability and scalability.
Keywords
Artificial Intelligence, Mouse monitoring, Behavior detection system, Zone tracking, Error analysis, Deep Learning.
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