Abstract: Ground reaction forces (GRF) measured during equine gait analysis are typically evaluated by analyzing discrete values obtained from continuous force-time data for the vertical, longitudinal and transverse GRF components. This paper describes a simple, temporo-spatial method of displaying and analyzing sagittal plane GRF vectors. In addition, the application of statistical parametric mapping (SPM) is introduced to analyse differences between contra-lateral fore and hindlimb force-time curves throughout the stance phase. The overall aim of the study was to demonstrate alternative methods of evaluating functional (a)symmetry within horses. Methods: GRF and kinematic data were collected from 10 horses trotting over a series of four force plates (120 Hz). The kinematic data were used to determine clean hoof contacts. The stance phase of each hoof was determined using a 50 N threshold. Vertical and longitudinal GRF for each stance phase were plotted both as force-time curves and as force vector diagrams in which vectors originating at the centre of pressure on the force plate were drawn at intervals of 8.3 ms for the duration of stance. Visual evaluation was facilitated by overlay of the vector diagrams for different limbs. Summary vectors representing the magnitude (VecMag) and direction (VecAng) of the mean force over the entire stance phase were superimposed on the force vector diagram. Typical measurements extracted from the force-time curves (peak forces, impulses) were compared with VecMag and VecAng using partial correlation (controlling for speed). Paired samples -tests (left v. right diagonal pair comparison and high v. low vertical force diagonal pair comparison) were performed on discrete and vector variables using traditional methods and Hotelling's tests on normalized stance phase data using SPM. Results: Evidence from traditional statistical tests suggested that VecMag is more influenced by the vertical force and impulse, whereas VecAng is more influenced by the longitudinal force and impulse. When used to evaluate mean data from the group of ten sound horses, SPM did not identify differences between the left and right contralateral limb pairs or between limb pairs classified according to directional asymmetry. When evaluating a single horse, three periods were identified during which differences in the forces between the left and right forelimbs exceeded the critical threshold ( < .01). Conclusions: Traditional statistical analysis of 2D GRF peak values, summary vector variables and visual evaluation of force vector diagrams gave harmonious results and both methods identified the same inter-limb asymmetries. As alpha was more tightly controlled using SPM, significance was only found in the individual horse although plots followed the same trends as discrete analysis for the group. Conclusions: The techniques of force vector analysis and SPM hold promise for investigations of sidedness and asymmetry in horses.
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The research explores a simple method of evaluating the ground forces exerted by a horse’s limbs during motion, focusing on asymmetries that could signal health or performance issues. It also introduces the use of statistical parametric mapping to analyze the force-time curves of the stance phase.
Research Method
The research involved gathering ground reaction forces (GRF) and kinematic data from 10 horses trotting over a series of four force plates at 120 Hz. The data gathered were used to assess clean hoof contacts and determine the stance phase of each hoof, with a threshold of 50 N.
The vertical and longitudinal GRF for each stance phase were plotted as force-time curves and as force vector diagrams, with vectors drawn from the center of pressure on the force plate at 8.3 ms intervals.
To facilitate visual evaluation, vector diagrams for different limbs were overlaid. Summary vectors representing the magnitude and direction of the mean force during the entire stance phase were added onto the force vector diagram.
Typical measurements extracted from force-time curves were compared to vector magnitude and direction with partial correlation, controlling for speed.
Results
The analysis indicated that the magnitude of force vectors is more influenced by the vertical force and impulse, while the direction is more influenced by the longitudinal force and impulse.
Using statistical parametric mapping (SPM) to evaluate data from all ten horses did not show differences between left and right contralateral limb pairs or directional asymmetry.
However, when analyzing a single horse, three periods were found where differences in forces between left and right forelimbs exceeded the critical threshold.
Traditional statistical analysis of 2D GRF peak values, summary vector variables and visual evaluation of force vector diagrams gave consistent results, both methods identifying the same inter-limb asymmetries. Due to the stricter control of the alpha using SPM, significance was only found in the individual horse.
Conclusions
The research concluded that both force vector analysis and statistical parametric mapping (SPM) could be useful in studying asymmetries and sidedness in horses.
While traditional methods of evaluation, such as vector variables and visual force vector diagrams, provided consistent results with the new technique, the SPM method offered stricter control and identified significant differences in an individual horse, proving its effectiveness for individual analyses.
Cite This Article
APA
Hobbs SJ, Robinson MA, Clayton HM.
(2018).
A simple method of equine limb force vector analysis and its potential applications.
PeerJ, 6, e4399.
https://doi.org/10.7717/peerj.4399
Centre for Applied Sport and Exercise Sciences, University of Central Lancashire, Preston, United Kingdom.
Robinson, Mark A
Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom.
Clayton, Hilary M
Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, MI, United States of America.
Conflict of Interest Statement
The authors declare there are no competing interests.
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