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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.19641975 |
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Table of Contents:
- <p class="MsoNormal"><span>Automated behavioural monitoring systems have changed metabolic cage studies by allowing continuous, objective, and high-throughput tracking of animal behaviour and physiology. This review consolidates findings from 30 key studies on how these systems operate, their applications, and their limitations. The technologies used include infrared beam-break sensors, RFID tracking, video analysis, and combinations of different sensors. These systems are mainly used in circadian biology, drug discovery, toxicology, disease modelling, and behavioural phenotyping . They offer clear benefits over manual observation, including reduced observer bias, on going data collection, and the ability to monitor animals in social groups. However, challenges remain, including accuracy during high activity, identifying individuals in groups, managing large amounts of data, and high costs. The field is moving quickly toward better computer vision, machine learning, and non-invasive monitoring, which could improve both research quality and animal welfare. Future developments will integrate multimodal data streams, cloud computing, and real-time analytics to enhance precision, scalability, and reproducibility in experiments..</span></p>