Abstract:
Fusion Motion Capture (FMC), a wearable motion capture system was developed, and applied
to the optimisation of athlete performance in alpine ski racing. In what may be a world first,
the three-dimensional movements of a skilled athlete (with less than 20 FIS1 points) skiing
through a complete training giant slalom racecourse were analysed.
FMC consists of multiple light weight sensors attached to the athlete including inertial
measurement units (IMUs), pressure sensitive insoles and a global position system (GPS)
receiver. The IMUs contain accelerometers, gyroscopes, and magnetometers. Limb
orientation and location are obtained by mathematically combining the most reliable data
from each sensor using fusion algorithms developed by the author. FMC fuses the signals
from the IMUs and GPS without the need for the post filtering, usually applied to motion
capture data, and therefore, maintains maximum bandwidth. The FMC results were stable and
relatively independent of motion type and duration unlike other inertial systems available in
2005, when the research was initiated.
Analysis of data collected from an athlete skiing giant slalom contradict the traditional „going
straight turning short? race strategy. The shortest path may not always be the fastest. Instead
each gate has a different optimum approach arc. Optimum turn radius increases with both
increasing speed and increasing terrain slope. The results also contradict laboratory
measurements of ski/snow sliding friction and suggest that snow resistance in giant slalom is
of similar importance to wind drag. In addition to gravity, the athlete increased speed using
the techniques of „lateral projection? and „pumping?.
Race performance was determined from the analysis of the athlete skiing through the entire
course. FMC proved, therefore, to be more suitable than traditional optical systems that are
practically limited to capturing small sections of a race course.
The athlete experienced high and rapidly fluctuating torques about all three axes of the lower
joints. This information could be useful in designing training programmes racecourses and
equipment to reduce knee injuries. Data driven animations and colour coded force vector
diagrams were developed to enhance athlete feedback. Inline skating data was also analysed.
