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Equine Vet J. 2009 Feb;41(2):112-7.

Evidence of the development of 'domain-restricted' expertise in the recognition of asymmetric motion characteristics of hindlimb lameness in the horse.

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Department of Veterinary Clinical Sciences, The Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire AL9 7TA, UK.



Visual assessment of horses' movements is subjective, affected by bias and dependent on the level of experience of the assessor. However, to date there are no data available on the ability of the human visual system to recognise (a)symmetry in moving objects.


To investigate, using visual lameness assessment, the limits of human perception and the ability of experienced and nonexperienced individuals to detect asymmetry in 2 moving objects simulating hindlimb lameness in the horse.


Twelve experienced individuals (equine and small animal clinicians), and 24 nonexperienced individuals (undergraduate veterinary students) were presented with computer simulations showing 2 'tuber coxae markers' created using data from both lame and nonperceptibly lame horses, as well as artificial data based on a sine wave. Individuals were asked to classify as symmetrical or asymmetrical, and then rank based on the grade of perceived asymmetry. Repeatability and learning effect were evaluated by repeating the tests on a subset of subjects.


The threshold for detection of movement asymmetry was found to be approximately 25% difference in amplitude between the 2 moving objects for all individuals. There was no significant difference between experienced and nonexperienced individuals in the ability to detect asymmetry in the simulations based on artificial data. However, the percentage of correct answers was higher for experienced compared to nonexperienced individuals for simulations based on data from real lame horses.


There was a significant difference between experienced and nonexperienced individuals in the ability to identify asymmetric movement based on the pattern seen in a lame horse, as opposed to an artificial pattern for which all individuals showed similar performance.


The study provides the basis for the development of computer simulations that could aid in training veterinarians in the diagnosis of lameness and, even, the objective assessment of expertise in this field.

[Indexed for MEDLINE]

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