Equine veterinary journal · 2026
Validation of a handheld smartphone markerless method for quantifying thoracolumbar flexion-extension range of motion in horses at trot.
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Christensen Maria Rosendahl, Kirkegaard Jakob, Berg Katja, Andresen Kristian Ringkjær, Skov Hansen Sabrina, Key Karsten
Аннотация
BACKGROUND: Back pain and poor performance in horses are difficult to assess objectively and thoracolumbar flexion-extension range of motion (FEROM) is not reliably evaluated by subjective observation alone. A handheld, smartphone-based markerless computer vision system (RealHorse®; RH) may enable objective clinical and field-based FEROM assessment but requires validation against an established optical motion capture reference system (Qualisys®; QS).
OBJECTIVES: To compare the accuracy and precision of RH relative to QS for measuring FEROM in horses trotting on a straight line and on a circle.
STUDY DESIGN: Cross-sectional comparative validation study.
METHODS: Fifty-nine horses were recorded trotting on a straight line; 23 of these were also recorded on a circle. Data were collected simultaneously using RH and QS, with a light source for manual frame-level synchronisation. The validation videos of horses were not used to train the RH algorithm. Agreement between RH and QS was analysed separately for straight-line and circular trot at stride and trial levels using mean signed error (MSE), mean absolute error (MAE), and Bland-Altman limits of agreement (LoA).
RESULTS: On the straight-line, stride-level MSE was -0.08°, MAE 0.96°, and LoA -2.49° to 2.32°. Trial-level agreement was high, with MSE -0.13°, MAE 0.44°, and LoA -1.22° to 0.94°. On the circle, stride-level MSE was -0.71°, MAE 1.14°, and LoA -3.17° to 1.74°. At the trial-level, variability was moderate (MSE -0.62°, MAE 0.78°, LoA -2.18° to 0.93°). Overall agreement was lower on the circle than on the straight-line and higher at trial-level than at stride-level.
CONCLUSIONS: Clinically, RH may support objective clinic and field-based monitoring of thoracolumbar flexion-extension range of motion, especially for repeated within-horse assessments, but decision thresholds remain to be established. Stride-level agreement between RH and QS was influenced by expected stride-to-stride variability, whereas averaging across strides improved agreement at the trial-level.
OBJECTIVES: To compare the accuracy and precision of RH relative to QS for measuring FEROM in horses trotting on a straight line and on a circle.
STUDY DESIGN: Cross-sectional comparative validation study.
METHODS: Fifty-nine horses were recorded trotting on a straight line; 23 of these were also recorded on a circle. Data were collected simultaneously using RH and QS, with a light source for manual frame-level synchronisation. The validation videos of horses were not used to train the RH algorithm. Agreement between RH and QS was analysed separately for straight-line and circular trot at stride and trial levels using mean signed error (MSE), mean absolute error (MAE), and Bland-Altman limits of agreement (LoA).
RESULTS: On the straight-line, stride-level MSE was -0.08°, MAE 0.96°, and LoA -2.49° to 2.32°. Trial-level agreement was high, with MSE -0.13°, MAE 0.44°, and LoA -1.22° to 0.94°. On the circle, stride-level MSE was -0.71°, MAE 1.14°, and LoA -3.17° to 1.74°. At the trial-level, variability was moderate (MSE -0.62°, MAE 0.78°, LoA -2.18° to 0.93°). Overall agreement was lower on the circle than on the straight-line and higher at trial-level than at stride-level.
CONCLUSIONS: Clinically, RH may support objective clinic and field-based monitoring of thoracolumbar flexion-extension range of motion, especially for repeated within-horse assessments, but decision thresholds remain to be established. Stride-level agreement between RH and QS was influenced by expected stride-to-stride variability, whereas averaging across strides improved agreement at the trial-level.