Effect of Perineural Anesthesia on the Centre of Pressure (COP) Path During Stance Phase at Trot in Sound Horses

An Investigation into the Effects of Changing Dorso-Plantar Hoof Balance on Equine Hind Limb Posture

Links between poor hind hoof balance, pathologies in the hind limb and associated altered posture have been suggested but not quantified. The hoof is proposed as a neuro-sensory organ responsible for informing equine stance with implications for musculoskeletal health in the hind limb and trunk of the horse. This study aims to quantify equine limb posture and its relationship with hoof balance. Twelve horses presenting with negative plantar angles were photographed and limb posture documented before and after the creation of positive plantar angles and improved three-dimensional proportions around the centre of rotation of the distal-interphalangeal joint, using farriery prosthetics. The results showed that horses presenting with negative plantar angles had canted-in postures and that farriery intervention had a significant effect on hind limb orientation in seven of these horses. There was a significant difference in metatarsal angle pre and post intervention with the mean for pre intervention being 81.3° ± 5.1 and post intervention being 88.0° ± 3.8 in the right hind and 74.4° ± 3.7 and 87.1° ± 2.9 in the left hind. The findings of this study support the hypothesis that the hoof balance informs equine stance and can play a role in affecting limb posture.

Development of an Artificial Neural Network for the Detection of Supporting Hindlimb Lameness: A Pilot Study in Working Dogs

Subjective lameness assessment has been a controversial subject given the lack of agreement between observers; this has prompted the development of kinetic and kinematic devices in order to obtain an objective evaluation of locomotor system in dogs. After proper training, neural networks are potentially capable of making a non-human diagnosis of canine lameness. The purpose of this study was to investigate whether artificial neural networks could be used to determine canine hindlimb lameness by computational means only. The outcome of this study could potentially assess the efficacy of certain treatments against diseases that cause lameness. With this aim, input data were obtained from an inertial sensor positioned on the rump. Data from dogs with unilateral hindlimb lameness and sound dogs were used to obtain differences between both groups at walk. The artificial neural network, after necessary adjustments, was integrated into a web management tool, and the preliminary results discriminating between lame and sound dogs are promising. The analysis of spatial data with artificial neural networks was summarized and developed into a web app that has proven to be a useful tool to discriminate between sound and lame dogs. Additionally, this environment allows veterinary clinicians to adequately follow the treatment of lame canine patients.