Centre of mass movement and mechanical energy fluctuation during gallop locomotion in the Thoroughbred racehorse

Abstract

SUMMARY During locomotion cyclical interchange between different forms of mechanical energy enhances economy; however, 100% efficiency cannot be achieved and ultimately some mechanical work must be performed de novo. There is a metabolic cost associated with fluctuations in mechanical energy, even in the most efficient animals. In this study we investigate the exchanges between different forms of mechanical energy involved in high-speed gallop locomotion in Thoroughbred race horses during over-ground locomotion using innovative, mobile data collection techniques. We use hoof-mounted accelerometers to capture foot contact times, a GPS data logger to monitor speed and an inertial sensor mounted over the dorsal spinous processes of the fourth to sixth thoracic vertebrae (the withers) of the horse to capture trunk movement with six degrees of freedom. Trunk movement data were used to estimate the movement of the centre of mass (CoM). Linear(craniocaudal, mediolateral and dorsoventral) and rotational (roll, pitch and heading) kinematic parameters (displacement, velocity and acceleration) were calculated for seven horses at gallop speeds ranging from 7 to 17 m s-1 during their regular training sessions. These were used to estimate external mechanical energy (potential energy and linear kinetic energy of the CoM) as well as selected components of internal energy (angular kinetic energy). Elastic energy storage in the limbs was estimated from duty factor, sine wave assumptions and published leg stiffness values. External mechanical energy changes were dominated by changes in craniocaudal velocity. Potential energy change, which was in phase with craniocaudal energy during the front limb stances, was small. Elastic energy storage in the limbs was small compared to the overall amplitude of fluctuation of external mechanical energy. Galloping at high speeds does not therefore fit classical spring mass mechanics.

The three-dimensional locomotor dynamics of African (Loxodonta africana) and Asian (Elephas maximus) elephants reveal a smooth gait transition at moderate speed

“…Hutchinson et al 2006), the motions of the head and forequarters largely move out of phase, which may cancel each other's motions out to some extent. Hence, we are confident that the errors induced by neglecting the head and limb motions in our method will be small (see also van den Bogert et al 1996;Pfau et al 2005Pfau et al , 2006 and should not change the major trends. These assumptions are validated by using multi-segment kinematic data (see electronic supplementary material).…”

“…We developed a novel multiple inertial sensor method, following Pfau et al (2005Pfau et al ( , 2006, incorporating three-dimensional accelerometers and gyroscopes to measure the three-dimensional body CM dynamics and the torso rotations of several elephants (here we use the term 'torso' to refer to the limbless body, rather than 'trunk', which in the case of elephants may confuse readers, or 'body', which we only use to refer to the whole body with all four limbs included). Hundreds of continuous strides were recorded as the elephants moved freely outside in open fields at a range of speeds (0.5-3.5 m s K1 ).…”

Walk–run classification of symmetrical gaits in the horse: a multidimensional approach

“…In addition to speed and limb-timing information (Robilliard et al 2007), the horses were equipped with a small inertial sensor (modified MT9, Xsens, Enschede, The Netherlands) attached underneath the most cranial edge of the saddle over the withers using a custom-made harness (Pfau et al 2005(Pfau et al , 2006. This sensor gives accurate six degrees of freedom movement information for the withers of the horse (Pfau et al 2005) and allows estimation of the centre of mass movement (Pfau et al 2006;Parsons et al 2008) and thus calculation of potential and kinetic energy fluctuations (Pfau et al 2006). From these data, the following features were calculated.…”

“…These were calculated from a combination of GPS speed (forwards velocity), inertial sensor velocity and vertical displacement data (see Pfau et al (2006) and Parsons et al (2008) for more details).…”

“…(Minetti et al (1999) reported values ranging from below 20% to below 50%.) Discrepancies might be due to the experimental methods, in particular GPS speed (Witte & Wilson 2004 and the use of a six degrees of freedom inertial sensor (see Pfau et al (2006) for more detail). Also, the horses in this study were ridden rather than manoeuvred 'in hand' or exercised on a treadmill.…”