Efficient and sensitive animal pain detection approaches are increasingly studied with the goal of improving animal welfare and monitoring the efficacy of treatment and rehabilitation. The aim of this study was to determine the potential of various behaviours as sensitive indicators of subtle inflammation states in equines. The long-term goal of this research is to understand how to objectively and remotely classify behaviours that are associated with inflammation using wearable inertial sensor technologies. This study represents a proof-of concept investigation to ascertain what behavioural indices might be important in long-term monitoring of mild bilateral inflammation and recovery with a view to translating the approach to a technology-enabled remote monitoring paradigm. Bilateral synovitis of the intercarpal joints was induced in seven equines using lipopoly saccharide (0.25 ng) at time zero. The horses were confined to stables and monitored intermittently over seven days by stable-fixed video cameras. White blood cell count, carpal circumference and food availability were recorded across the study. An ethogram was created to manually annotate behaviours from video footage following lameness induction at seven different timepoints across a 1-week period. Behaviour data were processed extracting the duration, frequency and variability of behaviours. One-way repeated measures ANOVA revealed a significant time effect for white blood cell count and behaviour switching. There were no significant changes in carpal circumferences and heart rate measures over the sampling period. Food availability appears to be an important contextual factor that should be considered in pain-related behavioural studies. We conclude that behaviour variability may be a promising indicator of subtle bilateral inflammation which should be further explored in larger controlled trials and different pain presentations. Future work will seek to optimise grouping of behaviours associated with inflammation that can be detected using wearable technologies for future remote monitoring protocols.