Thesis
The inertial properties of the German Shepherd
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2015
- Thesis identifier
- T14440
- Person Identifier (Local)
- 200774655
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- The police service dog has a long history stretching as far back as the 1400’s. One ofthe most popular dog breeds deployed by both the police and military has been theGerman Shepherd yet little is known about the morphology or body segmentparameters of this breed. Knowledge of these measures is essential for developingbiomechanical models that can guide clinicians in developing surgical interventions,injury treatment and prevention procedures. The aim of this thesis was to provide acomplete set of body segment parameters and inertial properties for the GermanShepherd. In addition, a canine motion capture suit and marker model was proposedfor use with this dog population.Morphometric measures and 3-dimensional inertial properties, including mass, centreof mass, moment of inertia and volume, were measured from 17 segments from eachof 6 German Shepherd police service dog cadavers. Measurements were performedwith frozen segments similar to the procedure on primates described by Reynolds(1974), on humans by Chandler et al. (1975) and on horses by Buchner et al. (1997).Using whole body mass and geometric modelling, multiple linear regression equationswere developed from the collected data so that they may be used to estimate segmentmasses and inertial tensors in living dogs. Using a custom Lycra suit and 44-markerfull-body marker set, kinematic data were collected to assess the practicality of themodel, to observe the dogs’ acceptance of the motion capture suit and to ensure foreand hind limb flexion/extension angles were comparable to those of other caninestudies.Using frozen cadavers, tissue loss was minimal at an average loss of 0.49% of totalbody mass. Hind limbs, at 6.8% of body mass, were 2.3% heavier than the forelimbs.Of the over 100 morphometric measures analysed, 33 were kept for inclusion in thelinear regression equations and joint centre estimations. Analyses of body mass alone,found that, except for the abdominal segment (r = .845, p≤.05), body mass did notcorrelate well with segmental masses. Similarly for moments of inertia, only themanus and pes produced predictive results using body mass alone. 11 regression equations were developed for predicting segment masses, and 33equations were developed for predicting moments of inertia about the three primaryaxes of each segment. Regression correlation analyses were summarized for eachsegment and a table of normalised average segment masses, centres of mass, radii ofgyration and segment densities was produced.Five police service dogs took part in the evaluation of the motion capture suit. Overallthe marker set and suit performed well and was well-received by dog/handler teams.The markers took very little time to apply, remained in place for the majority of trialsand the suit itself did not visibly affect the dog’s natural movement. An analysis of thekinematic data produced outputs showing characteristic patterns of flexion/extensionsimilar to those found in other canine research.With the development of regression equations for predicting segment mass andmoments of inertia combined with the proposed marker model and novel method ofmarker attachment, inverse dynamic analyses may be applied in future investigationsof canine mechanics, potentially guiding surgical procedures, rehabilitation andtraining for the German Shepherd breed.Key Words: Canine, German Shepherd, morphometry, kinematics, kinetics, inertialproperties, body segment parameter, segment model, moment of inertia, massdistribution.
- Advisor / supervisor
- Riches, Philip
- Stansfield, Ben
- Resource Type
- Note
- Previously held under moratorium from 30th November 2016 until 30th November 2021
- DOI
- Date Created
- 2015
- Former identifier
- 9912537087502996
- Funder
Relações
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PDF of thesis T14440 | 2021-07-02 | Público | Baixar |