Automated measurement of stress scores in video recordings of laboratory animals

• Applicant: Professorin Dr.-Ing. Dorit Merhof
• Subject Area: Sensory and Behavioural Biology ; Veterinary Medical Science
• Term: from 2020 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 321137804

During the first FOR 2591 funding period, the participating groups have analysed a number of methods for objective assessment of severity in animal experiments regarding their suitability as stress markers. The FOR 2591 has found out that image- and behaviour-based scores such as the mouse grimace scale (MGS) show a high correlation with the actual distress. Traditionally, these scores are taken manually, which results in high manual workload and potential bias. To speed up and simplify this assessment, the Institute of Imaging and Computer Vision has been working on the DFG-funded project “Automated measurement of stress scores in video recordings of laboratory mice” , which has been associated with the FOR 2591. The project goal of proving the general capability of automated methods for assessing image-based severity scores has been successfully reached. We were able to demonstrate that this process can be automated and can lead to a measurable reduction in scoring time required by veterinary staff.In the upcoming funding period, we aim at using the insights gained during the ongoing project to develop and validate a system for long-term monitoring of mice and rats in their home cages. The animals will be permanently monitored utilizing a combination of 2D and 3D cameras and behaviour parameters will be acquired. In cooperation with FOR 2591 partners, we will develop a recording setup that extends home cage types that are commonly used in laboratory animal science and can be effortlessly integrated into existing lab environments. Subsequently, we will develop algorithms for localization, identification and analysis of animals to allow assessment of the status of individual animals in group housings. To this end, we will analyse locomotor information such as travelled distance and location preference as well as individual behaviour such as rearing or self-grooming and social behaviour such as following or avoiding other group members. Changes to these behaviours as a consequence of animal experiments conducted by the project partners will be analysed to uncover statistical correlations between interventions and the resulting changes in behaviour. We will utilize established image processing methods as well as current advances from artificial intelligence and neural networks. The methods will be evaluated with selected partners from the FOR 2591 and subsequently validated together with all groups who work with mice and rats in multicentre studies. This way, we will assess the generalizability of the developed methods.

• DFG Programme: Research Units
• Subproject of: FOR 2591: Severity assessment in animal-based research