DISCUSSION
In this paper, we have presented a detailed description
and implementation of a technique for
computing lower limb rotations during level walking
using a simple marker system. For computing the
limb rotation angles, a system of axes was defined
based on a set of markers affixed to key anatomical
locations. Two factors were considered in choosing
the anatomical location. The first was to minimize
relative motion between the skin and underlying
bony structures, thereby satisfying the rigid body
assumption. For the skin-mounted markers as well
as the cuff-mounted markers, the rigid body assumption
was found to hold (on the average) to
within 2 3 mm. This did not have a significant effect
on the measured joint angle patterns. The second
consideration was to minimize the amount of manual
intervention needed to sort and track the marker
trajectories accurately. In video motion analysis
systems, it is common for the trajectories of closely
spaced markers to cross each other, thereby making
automatic tracking by the computer extremely difficult.
Manual intervention is often necessary to
identify trajectories of closely spaced markers
whose paths intersect. In gait analysis, the trajectories
of markers placed on the foot present problems
due to their relative proximity to each other.
Therefore, in the present system, only two markers
were used on the foot to define limiting the measurement
of ankle joint motion to flexion-extension
and internakxternal rotation. Due to the geometry
and the size of the foot segment, adding another
marker to measure eversion-inversion angle would
complicate the data analysis. Further, given the finite
accuracy and resolution of the motion analysis
system, the estimates of inversion-eversion may
not be sufficiently accurate to be of any practical
use. By limiting the number of markers on the foot
to two, the time required for data analysis is substantially
reduced, which renders the system attractive
for use in routine clinical gait evaluation.