An automated system for the assessment of pain and wellbeing in laboratory mice

Principal Investigator: Prof Johannes Bohacek

Co-Investigators: Dr Oliver Sturman, Prof Thomas Nevian, Mr Niek Andresen, Dr Katharina Hohlbaum, Prof Lars Lewejohann, Dr Ruslan Rust

Grant Amount: CHF 480'000.-

Keywords: Machine Learning, Welfare Monitoring, Grimace Scale, 3D Gait Analysis, Unsupervised Behavioural Clustering, Ethological Monitoring, Pain Assessment, Automated Cageside Assessment

Animal Use: Yes

Application Abstract:
Monitoring the well-being of mice in research labs is often overlooked, and current methods rely on subjective observations, leading to potential biases and variations between different observers. Recent advancements in machine vision and learning tools offer a solution by automating and standardizing these measures. This project aims to create an all-in-one automated platform (both hardware and software) for monitoring animal welfare. It will include 3D gait analysis, the grimace scale, assessment of ethological behaviors, and detailed analysis of behavioral patterns. This platform can be easily implemented in research labs, providing a more comprehensive evaluation of how experimental procedures, such as surgeries and analgesia, impact the health of mice. By filling a technological gap, this project enhances the accuracy and reliability of animal welfare monitoring, allowing for consistent data across different research settings. Ultimately, it supports the establishment of universally accepted standards for the care of mice undergoing various experimental procedures worldwide.