Introduction to Sports Biomechanics: Analysing Human Movement ...

Data errors
There are several ‘mathematical’ models that calculate body segment parameters
from standard anthropometric measurements, such as segment lengths and circumferences.
Some of these models result in large errors even in estimates of segment
volumes. Others are very time-consuming, requiring up to 200 anthropometric
measurements, which take at least an hour or two to complete. All these models require
density values from other sources, usually cadavers, and most of them assume constant
density throughout the segment, or throughout large parts of the segment.
The greatest problems in body segment data occur for moments of inertia. There
are no simple yet accurate methods of measuring segmental moments of inertia for a
living person. Many model estimations are either very inaccurate or require further
validation. A relative error of 5% in segmental moments of inertia may be quite common.
Norms or linear regression equations are often used, but these should be treated
with caution as the errors involved in their use are rarely fully assessed. It may be
necessary to allow for the non-linear relationships between segmental dimensions and
moment of inertia values.
Uncertainties, also referred to as errors, in the results of biomechanical data processing
can be large, particularly for computation of kinetic variables. This is mainly because of
errors in the body segment data and linear and angular velocities and accelerations, and
the combination of these errors in the inverse dynamics equations. If such computations
are to be attempted, scrupulous adherence to good experimental protocols is
essential. A rigorous assessment of the processing techniques is also necessary. The topic
of error analysis is a very important one and the value of sports biomechanical measurements
cannot be assessed fully in the absence of a quantification of the measurement
error. The accuracy of the measuring system and the precision of the measurements
should be assessed separately. Error propagation in calculations can be estimated using
standard formulae (see Challis, 2007; Further Reading, page 152).
PROJECTILE MOTION
QUANTITATIVE ANALYSIS OF MOVEMENT
In this section, we illustrate an important example of linear (in fact, curvilinear) motion
– the motion of a projectile in the air. Projectiles are bodies launched into the air that
are subject only to the forces of gravity and air resistance. Projectile motion occurs
frequently in sport and exercise activities. Often the projectile involved is an inanimate
object, such as a shot or golf ball. In some activities the sports performer becomes the
projectile, as in the long jump, high jump, diving and gymnastics. An understanding of
the mechanical factors that govern the flight path or trajectory of a projectile is, therefore,
important in sports biomechanics. The following discussion assumes that the
effects of aerodynamic forces – both air resistance and more complex lift effects – on
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