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A quantitative evaluation of physical and digital approaches to centre of mass estimation

Macaulay, S; Hutchinson, J R; Bates, K T


S Macaulay

J R Hutchinson

K T Bates


Centre of mass is a fundamental anatomical and biomechanical parameter. Knowledge of centre of mass is essential to inform studies investigating locomotion and other behaviours, through its implications for segment movements, and on whole body factors such as posture. Previous studies have estimated centre of mass position for a range of organisms, using various methodologies. However, few studies assess the accuracy of the methods that they employ, and often provide only brief details on their methodologies. As such, no rigorous, detailed comparisons of accuracy and repeatability within and between methods currently exist. This paper therefore seeks to apply three methods common in the literature (suspension, scales and digital modelling) to three 'calibration objects' in the form of bricks, as well as three birds to determine centre of mass position. Application to bricks enables conclusions to be drawn on the absolute accuracy of each method, in addition to comparing these results to assess the relative value of these methodologies. Application to birds provided insights into the logistical challenges of applying these methods to biological specimens. For bricks, we found that, provided appropriate repeats were conducted, the scales method yielded the most accurate predictions of centre of mass (within 1.49 mm), closely followed by digital modelling (within 2.39 mm), with results from suspension being the most distant (within 38.5 mm). Scales and digital methods both also displayed low variability between centre of mass estimates, suggesting they can accurately and consistently predict centre of mass position. Our suspension method resulted not only in high margins of error, but also substantial variability, highlighting problems with this method.


Macaulay, S., Hutchinson, J. R., & Bates, K. T. (2017). A quantitative evaluation of physical and digital approaches to centre of mass estimation. Journal of Anatomy, 231(5), 758-775.

Journal Article Type Article
Acceptance Date Jun 2, 2017
Publication Date Aug 15, 2017
Deposit Date Dec 12, 2017
Publicly Available Date Dec 12, 2017
Print ISSN 0021-8782
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 231
Issue 5
Pages 758-775
Public URL


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