Abstract: Equine training methods, and consequently, performance times have improved little since the last decades. With advances in measuring signals on-line by means of several new technologies and analytical procedures, and processing these signals immediately with strong and compact processors, it may be possible to develop new training methods. In this research, the objective was to explore the possibilities of using modern model-based algorithms to control the heart rate of horses (bpm) on-line by means of the control input running speed (km/h). Forty-five experiments with five horses and four riders were carried out to generate measurements of physiological status during running. The dynamical characteristics of each horse were quantified using linear discrete transfer function models. The dynamic response of heart rate to step changes in running speed were accurately described. In 90% of the cases, a first-order model gave the best fit. For 69% of the models, the r2 was higher than 0.90 and for 34% of the models, the r2 was even higher than 0.95. In a next step, the model-based algorithm was evaluated by controlling cardiac responses of two horses (horses 2 and 4) to a pre-defined trajectory. The model parameters were kept constant. On average, the error between the defined target trajectory in heart rate and the actual controlled heart rate ranged between 0.2 and 1.4 bpm for the whole target heart rate trajectory. During the steady-state part of the trajectory the average error was maximum 1.1 bpm. In the transient from one steady-state heart rate to another level, the error could increase on average up to 5 bpm. In the future, the combination of on-line measured bioresponses with real-time analysis can be used for adjusting the work load of the horse, during training, directly to the immediate needs of horse (welfare) and trainer (performance).

Abstract: The interaction of horses with humans is a dynamic state, but it is not clearly understood how horses perceive humans. Nervousness is transmissible from humans to horses indicated by increased horse heart rate (HR), however no studies have investigated whether horses can differentiate between humans who are physiologicallystressed (eg. after exercising) as opposed to psychologically-stressed (eg. feeling nervous/afraid). Horses (N=10) were randomly subjected to each of four treatments: 1) no human [control], 2) a calm human comfortable around horses [CALM; N=2 humans], 3) a physically-stressed human [PHYS; human exercised to reach 70% of maximum HR; N=2 humans], and 4) a psychologically-stressed human [PSYCH; human who was nervous around horses; N=14 humans]. Humans ranked themselves on a scale of 1-10 for their nervousness around horses. Both humans and horses were equipped with a HR monitor. Behavioural observations of the horses [gait, head position relative to the withers, distance from human, orientation toward human] were recorded live. Horses were allowed to wander loose in a round pen for 5 minutes of baseline recordings, at which time the human subject entered the round pen, stood in the centre and placed a blindfold over his/her eyes. The human remained in the centre of the round pen for an additional 5 minutes. Horse HR during control did not differ from when the human was present in the CALM and PSYCH treatment, and was lower during the PHYS treatment (51a vs 54a vs 55a vs 45b bpm for control, CALM, PSYCH and PHYS respectively; a,b differ p<0.0001). Over the 5 minute test period, horse HR decreased in PHYS and PSYCH (p<0.01) whereas it increased in CALM (p<0.0001). Horse HR decreased with increasing human rank of nervousness around horses (p=0.0156), and horses stood nearer to the human when they faced the human (p<0.0001) regardless of treatment. Horses moved at a faster gait in the control treatment, and their gait was slowest in the PSYCH treatment (p<0.0001), and the horse’s head position was lower in the PHYS and PSYCH treatments compared to CALM or baseline (p< 0.0001). A lower horse head position was positively correlated to a lower horse HR (p<0.0001) and negatively correlated to horse age (p<0.0001). Human HR was affected by treatment, with PHYS having the highest HR (p<0.0001). Human HR increased when the horse was facing away from the human, even though the human was blindfolded (p=0.0395). Overall, horses appear to be influenced by the physiological and psychological state of a human without any direct contact. Horses’ posture does reflect their physiological state. Understanding how horses react to human physiological and psychological states is especially important in equine-assisted activities, where the response of the horse has specific implications for the human participant.

Abstract: The relationship between facial hair whorl position and reactivity, as assessed by behavioural measures (handling score = HS; startle reaction to a suddenly appearing novel object = SR; latency to touch a novel object = LNO) and heart rate measures (mean HR; increase in heart rate = IHR) were studied using 55 Konik horses reared either under conventional stable conditions or in the forest reserve. Horses were classified into four groups according to the whorl position and/or shape: (1) high, single whorl above the top eye line, n = 9; (2) medium, single whorl between the top and the bottom eye line, n = 30; (3) low, single whorl below the bottom eye line, n = 10; and (4) elongated or double whorl, n = 6. Horses with a high whorl position demonstrated a lesser degree of manageability as expressed by a lower HS compared to individuals with medium (P = 0.002) or low whorl positions (P = 0.016). Horses with different whorl positions did not differ significantly in their startle response to a suddenly appearing novel object (P = 0.685). The horses with an elongated or double whorl, which appeared only in the forest group, took significantly longer to approach the novel object than horses with medium (P = 0.006) or low (P = 0.005) whorl positions. No significant differences in mean HR and IHR between groups (HR: P = 0.629 and IHR: P = 0.214) were found. In conclusion, this study supports the relationship between the position of the hair whorl on the horses' head and their manageability during handling, as well as the latency to approach an unknown object.

Abstract: The aim of the study was to investigate whether heart rate variability (HRV) could assess alterations of the autonomic nervous system (ANS) at different levels of excitement. The behavioural and physiological responses of 20 warmblood horses to a challenging ground exercise task were studied. Prior to the experiment, the horses were evaluated at rest and during forward walking (FW). The horses were then forced to move backwards continuously during 3 min according to a standardised protocol (BW1). Subsequently, the horses were exposed to two training sessions, after which the backward walking (BW2) was re-evaluated. Heart rate (HR) and HRV-parameters such as the standard deviation of the beat-to-beat intervals (SDRR), the low (LF; sympathetic tone) and high frequency (HF) component of HRV (HF; parasympathetic tone) and their ratio (LF/HF; index representing the sympatho-vagal balance) were sampled at rest, and during FW, BW1 and BW2. Stress-related behaviour during BW1 and BW2 was determined from video recordings. The results of the different evaluations were compared to each other. Compared to rest and FW, the first backward experiment induced a significant rise in HR, LF and LF/HF and a significant decrease of HF. SDRR decreased from both FW and rest with only the latter reaching significance. In BW2 after the training sessions, HR and the parameters of the sympathetic branch of the ANS (LF, LF/HF) were decreased and the vagal tone (HF) increased compared to BW1; all changes were significant. The duration of stress indicating behavioural patterns revealed also a significant decrease of excitement after the training, when backward walking did not differ from forward walking in any parameter. Correlations between HRV-parameters and stress indicating behaviour as well as HR were found. We conclude that the HRV-parameters LF and HF are valuable measures to quantify sympatho-vagal balance, which allows a more precise assessment of the responses of HR and SDRR to mental stress during low intensity exercise.

Abstract: Current definitions of horse personality traits are rather vague, lacking clear, universally accepted guidelines for evaluation in performance tests. Therefore, the aim of the present study was to screen behavioural and physiological measurements taken during riding for potential links with scores the same horses received in the official stallion performance test for rideability and personality traits. Behaviour, heart rate (HR) and HR variability from thirty-six stallions participating in a performance test were recorded repeatedly during their performance test training. Using the coefficient of determination, regression analysis revealed that about 1/3 of variation (ranging between r = 0.26 (“constitution” (i.e. fitness, health)) and r = 0.46 (rideability)) in the personality trait scores could be explained by selecting the three most influential behaviour patterns per trait. These behaviour patterns included stumbling (with all traits except character), head-tossing (temperament, rideability), tail-swishing (willingness to work), involuntary change in gait (character) and the rider's use of her/his hands (constitution, rideability), voice (temperament) or whip (constitution). Subsequent mixed model analysis revealed a significant (P < 0.05) influence of the behaviour pattern “horse-induced change in gait” on character (-0.98 ± 0.31 scores per additional occurrence of change in gaits), of head-tossing (-0.25 ± 0.08 scores) and rider's use of voice (-0.51 ± 0.25; P = 0.0594) on temperament, and of stumbling on each of the following: willingness to work (-2.5 ± 1.2), constitution (-2.5 ± 1.2 scores; P = 0.0516) and rideability scores (-3.3 ± 1.4). In addition, constitution scores tended (P = 0.0889) to increase with higher low frequency/high frequency heart rate variation ratios (LF/HF), indicating a shift towards sympathetic dominance and thus a higher stress load in horses with higher scores for constitution. Rideability scores from the training phase were also significantly influenced by head-tossing (-0.5 ± 0.1), and in addition rideability scores from the final test were influenced by the training rider, ranging between average estimated rideability scores of 6.8 ± 0.4 for one training rider and 8.36 ± 0.3 scores for another training rider. Horses ridden with their nose-line predominantly behind the vertical received higher scores for rideability (8.3 ± 0.3) than horses ridden with their nose-line at the vertical (7.7 ± 0.2). These findings indicate that either judges perceive horses to have a better rideability when they readily offer a more extreme poll flexion, or that riders make use of horses’ better rideability by imposing a more extreme poll flexion. Several of the above described associations, but also of the non-existing links (e.g. no association between shying or heart rate and temperament) between behaviour patterns and scores for personality traits are rather surprising, warranting further investigation regarding the underlying causes of these relationships. Some of these behaviour patterns should be considered when redesigning the current guidelines for evaluation of personality traits during breeding horse performance tests, ultimately leading to improved genetic selection for equine personality traits. However, ethical implication of defining aversive behaviour such as head-tossing as an indicator of, for example, poor temperament, should not be neglected when devising new guidelines: such aversive behaviour may in fact be an indication of inadequate training techniques rather than poor horse personality.