An Automated, Home-Cage, Video Monitoring-based Mouse Frailty Index Detects Age-associated Morbidity in C57BL/6 and Diversity Outbred Mice.

Frailty indexes (FIs) provide quantitative measurements of nonspecific health decline and are particularly useful as longitudinal monitors of morbidity in aging studies. For mouse studies, frailty assessments can be taken noninvasively, but they require handling and direct observation that is labor-intensive to the scientist and stress inducing to the animal. Here, we implement, evaluate, and provide a refined digital FI composed entirely of computational analyses of home-cage video and compare it to manually obtained frailty scores in both C57BL/6 and genetically heterogeneous Diversity Outbred mice. We show that the frailty scores assigned by our digital index correlate with both manually obtained frailty scores and chronological age. Thus, we provide an automated tool for frailty assessment that can be collected reproducibly, at scale, without substantial labor cost.

3D mouse pose from single-view video and a new dataset.

We present a method to infer the 3D pose of mice, including the limbs and feet, from monocular videos. Many human clinical conditions and their corresponding animal models result in abnormal motion, and accurately measuring 3D motion at scale offers insights into health. The 3D poses improve classification of health-related attributes over 2D representations. The inferred poses are accurate enough to estimate stride length even when the feet are mostly occluded. This method could be applied as part of a continuous monitoring system to non-invasively measure animal health, as demonstrated by its use in successfully classifying animals based on age and genotype. We introduce the Mouse Pose Analysis Dataset, the first large scale video dataset of lab mice in their home cage with ground truth keypoint and behavior labels. The dataset also contains high resolution mouse CT scans, which we use to build the shape models for 3D pose reconstruction.