LabGrymace: Automated Analysis of Mouse Grimace for Quantitative Assessment of Pain Dynamics

Authors

Dong, W., Moehn, K. M., Ronan, E. A., Hu, Y., Emrick, J. J., Ye, B.

Abstract

Accurate assessment of pain in animal models is essential for understanding pain mechanisms, developing analgesics, and ensuring animal welfare. The Mouse Grimace Scale (MGS) provides a sensitive, non-invasive measure of spontaneous pain by quantifying pain-related facial expressions, but its utility is limited by labor-intensive manual scoring, observer variability, and reliance on static images that fail to capture the temporal dynamics of facial behavior. Existing automated approaches improve throughput but typically rely on highly standardized imaging conditions, selected viewing angles, and static facial appearance, while providing limited temporal resolution and little insight into the relative contributions of individual facial action units. Here, we introduce LabGrymace, an open-source, artificial intelligence-powered framework for automated, frame-by-frame analysis of pain-related facial dynamics in freely moving mice. Built on the LabGym behavioral analysis platform, LabGrymace uses deep-learning-based facial feature detection and tracking to quantify ear, eye, and nose movements continuously from video recordings. To generate a quantitative pain metric and facilitate reproducibility, we calibrated facial dynamics against graded chemogenetic activation of nociceptors and identified the kinematic features most strongly associated with pain intensity. These features were integrated into a weighted composite pain score that reflects the differential contributions of individual facial action units. LabGrymace accurately classified pain-related facial actions and generated continuous pain scores without manual frame selection or restrictive recording conditions. The resulting pain scale exhibited dose-dependent responses generalized across distinct pain modalities, including visceral pain induced by MgSO and somatic pain induced by capsaicin. By combining automated facial-feature analysis with quantitative temporal modeling, LabGrymace provides an objective, scalable, interpretable, and flexible tool for assessing spontaneous pain in laboratory mice.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 07 Aug 2026.

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