Inertial properties of the German Shepherd Dog

O. Yvette Jones, Silvia U. Raschke, Philip E. Riches

Research output: Contribution to journalArticle

Abstract

One of the most popular dog breeds deployed by both the police and military has been the German Shepherd yet little is known about the morphology or body segment parameters of this breed. Such measures are essential for developing biomechanical models which, in turn, may guide clinicians in developing surgical interventions, injury treatment and prevention procedures. This paper provides a complete set of body segment parameters and inertial properties for the German Shepherd. Morphometric measures and 3-dimensional inertial properties, including mass, centre of mass, moment of inertia and volume, were measured from 17 segments from 6 German Shepherd police service dog cadavers. Using whole body mass and geometric modelling, 11 regression equations were developed for predicting segment masses, and 33 equations were developed for predicting moments of inertia. Using these data, inverse dynamic analyses may be applied in future investigations of canine mechanics, guiding surgical procedures, rehabilitation and training especially for the German Shepherd breed but potentially for other breeds too.
LanguageEnglish
Article numbere0206037
Number of pages14
JournalPLOS One
Volume13
Issue number10
DOIs
Publication statusPublished - 19 Oct 2018

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German Shepherd
Police
Law enforcement
Dogs
police
dogs
Intraoperative Complications
Mechanics
breeds
Cadaver
Patient rehabilitation
Canidae
service dogs
Rehabilitation
rehabilitation (people)
dog breeds
mechanics
surgery
Therapeutics

Keywords

  • morphology
  • body segment parameters
  • german shepherd dog
  • surgical procedures
  • biomechanics

Cite this

Jones, O. Yvette ; Raschke, Silvia U. ; Riches, Philip E. / Inertial properties of the German Shepherd Dog. In: PLOS One. 2018 ; Vol. 13, No. 10.
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Inertial properties of the German Shepherd Dog. / Jones, O. Yvette; Raschke, Silvia U.; Riches, Philip E.

In: PLOS One, Vol. 13, No. 10, e0206037, 19.10.2018.

Research output: Contribution to journalArticle

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