Evaluation of thermal pattern distributions in racehorse saddles using infrared thermography.
Authors: Soroko Maria, Zaborski Daniel, Dudek Krzysztof, Yarnell Kelly, Górniak Wanda, Vardasca Ricardo
Journal: PloS one
Summary
# Editorial Summary: Thermal Pattern Evaluation in Racehorse Saddles Infrared thermography offers a non-invasive method to assess how rider mass and saddle characteristics influence weight distribution across the saddle panels—a parameter that directly affects comfort and performance in racehorses. Researchers used IRT to capture thermal images of saddle panels across six examinations on 18 racehorses ridden by four different riders, analysing six regions of interest on each panel using thermal indicators including maximum temperature differential (ΔTmax), symmetry indices, and bridging/rocking patterns. Nearly a quarter of measurements (23.1%) showed suboptimal fit with ΔTmax exceeding 2°C, with significant variation between individual riders: one rider consistently generated higher temperature differentials (p<0.001) and produced a front-weighted saddle pressure pattern in 41.5% of rides, whilst another showed predominant rear weighting (85.7%). The findings reveal that rider biomechanics and mass distribution significantly affect saddle fit independent of saddle design itself (p<0.001), suggesting that achieving optimal load distribution requires consideration of the rider–saddle–horse interaction rather than saddle fit in isolation. For practitioners, this highlights the value of IRT as a rapid, objective assessment tool to identify problematic pressure patterns and guide interventions—whether through rider training, saddle adjustment, or alternative saddle selection—particularly when subjective observations alone may miss asymmetrical or focal pressure zones.
Read the full abstract on PubMed
Practical Takeaways
- •Infrared thermography can be used as a non-invasive, on-field tool to identify saddle fit problems after training—a ΔTmax >2°C warrants saddle reassessment
- •Rider-related factors are as critical as saddle design; same saddle may fit differently depending on who rides—consider rider assessment alongside saddle fitting
- •Thermal imaging provides objective data on pressure distribution patterns (bridging, rocking, lateral shifts) that can guide saddle adjustment or replacement decisions
Key Findings
- •Infrared thermography detected incorrect saddle fit in 23.1% of measurements, defined by ΔTmax >2°C between warmest and coolest regions
- •Significant relationships existed between individual riders and saddle fit quality (p<0.001), as well as between saddle fit and individual horses (p<0.001)
- •Rider A produced significantly higher ΔTmax values and front-saddle thermal patterns (41.5%), while rider C showed predominantly back-saddle patterns (85.7%)
- •Thermal pattern distribution indicators (bridging/rocking, right/left, front/back) successfully quantified load distribution differences attributable to rider mass and position