Biomedical Engineering Reference
In-Depth Information
(a)
(b)
(c)
Fig. 15.2
Representation of a sample display of
(a)
virtual footprints,
(b)
a stick figure, and
(c)
a
virtual human to be used as visual cues to modify the gait patterns of patients
walk through a virtual landscape, providing information to the patient about joint
angles in the different phases of the gait cycle (see Fig.
15.2
b). It is possible that a
humanoid figure would be even more salient for synchronization purposes, so high-
definition virtual humans or avatars may be an appropriate choice (see Fig.
15.2
c).
Finally, a third-person display of dual figures could be presented: the desired move-
ment might be specified by a virtual human driven by a computational model or
an avatar driven by motion capture data, while visual feedback is provided by an
avatar yoked to the patient. This scenario would not only give the patient immediate
feedback about their own performance, but would provide a model character for on-
line movement comparison. Investigations into these types of stimuli are currently
underway in the Virtual Environment for Assessment and Rehabilitation Laboratory
(VEAR Lab) at the University of North Carolina at Greensboro.
15.2.2 Dynamic Measures for Assessing Global Functional
Mobility Using VR
The previous examples illustrate the potential strength of VR applications for rehabil-
itation; namely, the opportunity to manipulate environmental information to probe
the control parameters and index the dynamics of functional mobility at the local
level of the step cycle. VR also lends itself to the flexible design of assessment pro-
tocols that yield continuous measures of behavior at a more global level, such as the
locomotor trajectory.
