Hydrotherapy has been utilized in horse rehabilitation programs for over four decades. However, a comprehensive description of the swimming cycle of horses is still lacking. One of the challenges in studying this motion is 3D underwater motion capture, which holds potential not only for understanding equine locomotion but also for enhancing human swimming performance. In this study, a marker-based system that combines underwater cameras and markers drawn on horses is developed. This system enables the reconstruction of the 3D motion of the front and hind limbs of six horses throughout an entire swimming cycle, with a total of twelve recordings. The procedures for pre- and post-processing the videos are described in detail, along with an assessment of the estimated error. This study estimates the reconstruction error on a checkerboard and computes an estimated error of less than 10 mm for segments of tens of centimeters and less than 1 degree for angles of tens of degrees. This study computes the 3D joint angles of the front limbs (shoulder, elbow, carpus, and front fetlock) and hind limbs (hip, stifle, tarsus, and hind fetlock) during a complete swimming cycle for the six horses. The ranges of motion observed are as follows: shoulder: 17 ± 3°; elbow: 76 ± 11°; carpus: 99 ± 10°; front fetlock: 68 ± 12°; hip: 39 ± 3°; stifle: 68 ± 7°; tarsus: 99 ± 6°; hind fetlock: 94 ± 8°. By comparing the joint angles during a swimming cycle to those observed during classical gaits, this study reveals a greater range of motion (ROM) for most joints during swimming, except for the front and hind fetlocks. This larger ROM is usually achieved through a larger maximal flexion angle (smaller minimal angle of the joints). Finally, the versatility of the system allows us to imagine applications outside the scope of horses, including other large animals and even humans.

Aquatic training has been integrated into equine rehabilitation and training programs for several decades. While the cardiovascular effects of this training have been explored in previous studies, limited research exists on the locomotor patterns exhibited during the swimming cycle. This study aimed to analyze three distinct swimming strategies, identified by veterinarians, based on the propulsion phases of each limb: (S1) two-beat cycle with lateral overlap, (S2) two-beat cycle with diagonal overlap, and (S3) four-beat cycle. 125 underwater videos from eleven horses accustomed to swimming were examined to quantify the differences in locomotor patterns between these strategies. Initially, a classifier was developed to categorize 125 video segments into four groups (CatA to CatD). The results demonstrated that these categories correspond to specific swimming strategies, with CatA aligning with S1, CatB with S2, and CatC and CatD representing variations of S3. This classification highlights that two key parameters, lateral and diagonal ratios, are indeed effective in distinguishing between the different swimming strategies. Additionally, coordination patterns were analyzed in relation to these swimming strategies. One of the primary findings is the variability in swimming strategies both within and between individual horses. While five horses consistently maintained the same strategy throughout their swimming sessions, six others exhibited variations in their strategy between laps. This suggests that factors such as swimming direction, pauses between laps, and fatigue may influence the selection of swimming strategy. This study offers new insights into the locomotor patterns of horses during aquatic training and has implications for enhancing the design of rehabilitation protocols.

Equine swimming is increasingly used for injury prevention and rehabilitation, but objective analysis of movement during swimming remains limited compared to land-based locomotion. Spatiotemporal parameters are essential for evaluating therapeutic outcomes, yet capturing these parameters is technically challenging due to difficulties in observing limb motion in water. Inertial sensors, already widely applied in equine science, offer a promising solution for measuring swimming kinematics objectively. The objective of this study was to evaluate the reliability of inertial sensors placed on equine distal limbs in detecting key spatiotemporal events during swimming by comparing it with video-based detection made by veterinarians. For the duration of the hindlimb swimming cycle, 24 data values were analysed and showed an “excellent” agreement, with an intraclass correlation coefficient = 0.96, 95% CI: 0.904–0.983, and Bland–Altmann analysis showed an upper limit of agreement of 50 ms (95% CI: 70 ms, 30 ms) and lower one of −60 ms (95% CI: −40 ms, −80 ms). The estimates of the “swimming” duty factor of the hindlimb (n = 24) demonstrated “moderate” to “excellent” with intraclass correlation of 0.82 (95% CI: 0.625–0.920) and limits of agreement of 4.39% (95% CI: 6.21%, 2.53%) and −5.28% (95% CI: −3.42%, −7.14%). The results of the forelimb were mixed, suggesting that the cycle duration and “swimming” duty factor parameters determined for this limb should be used with caution. Overall, the findings confirm that inertial sensors, particularly on the hindlimbs, provide reliable spatiotemporal measurements and are well suited for studying equine swimming.