Abstract
Simple SummaryDetecting horse state after exercise is critical for maximizing athletic performance. The horse’s response to fatigue includes exercise termination or exercise continuation at a lower intensity, which significantly limit the results achieved in races and equestrian competition. As conventional methods of detecting and quantifying exercise effort have shown some limitations, infrared thermography was proposed as a method of contactless detection of exercise effect. The promising correlation between body surface temperature and exercise-dependent blood biomarkers has been demonstrated. As the application of conventional thermography is limited by low specificity, advanced thermal image analysis was proposed here to visualize the link between blood biomarkers and texture of thermal images. Twelve horses underwent standardized exercise tests for six consecutive days, and both thermal images and blood samples were collected before and after each test. The images were analyzed using four color models (RGB, red-green-blue; YUV, brightness-UV-components; YIQ, brightness-IQ-components; HSB, hue-saturation-brightness) and eight texture-features approaches, including 88 features in total. In contrast to conventional temperature measures, as many as twelve texture features in two color models (RGB, YIQ) were linked with blood biomarker levels as part of the horse’s response to exercise.As the detection of horse state after exercise is constantly developing, a link between blood biomarkers and infrared thermography (IRT) was investigated using advanced image texture analysis. The aim of the study was to determine which combinations of RGB (red-green-blue), YUI (brightness-UV-components), YIQ (brightness-IQ-components), and HSB (hue-saturation-brightness) color models, components, and texture features are related to the blood biomarkers of exercise effect. Twelve Polish warmblood horses underwent standardized exercise tests for six consecutive days. Both thermal images and blood samples were collected before and after each test. All 144 obtained IRT images were analyzed independently for 12 color components in four color models using eight texture-feature approaches, including 88 features. The similarity between blood biomarker levels and texture features was determined using linear regression models. In the horses’ thoracolumbar region, 12 texture features (nine in RGB, one in YIQ, and two in HSB) were related to blood biomarkers. Variance, sum of squares, and sum of variance in the RGB were highly repeatable between image processing protocols. The combination of two approaches of image texture (histogram statistics and gray-level co-occurrence matrix) and two color models (RGB, YIQ), should be considered in the application of digital image processing of equine IRT.
Highlights
Detecting animal fatigue after exercise is critical to ensure maximal performance in athletes [1]
To explore further, repeated exercise was evaluated to determine which features of image texture are related to blood biomarkers of exercise effect
The mean ± standard deviation (SD) values of hematological and biochemical blood biomarkers are summarized in Supplementary Table S1
Summary
Detecting animal fatigue after exercise is critical to ensure maximal performance in athletes [1]. Horses are considered the most utilized athletes within the animal kingdom. Huge investments of time and money are made to increase their exercise capacity and improve their overall performance during training [2–4]. Exercise-induced fatigue occurs after repeated exercise with insufficient recovery [5,6] and/or prolonged [7,8] or highintensity exercise [4,9]. Exercise-induced fatigue results in temporary loss of strength and energy, leading to decreased capacity for physical activity and a decline in the execution of horses’ athletic skills [2,10]. A horse’s response to fatigue can include exercise termination or exercise continuation at a lower intensity [4,11], both of which significantly limit the results achieved in races [4,9] and the equestrian Olympic games [12–14]. Exercise should include evaluation of horse state in order to avoid fatigue [2–4]. Performance decrease is associated with a decrease in energy source in muscles and hormonal changes causing mental stress and welfare disturbance [12,15]
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