Biomedical Engineering Reference
In-Depth Information
Table 8.1 Summary of gait parameters and their potential use in walking in VR
Parameters
Methods
Examples of applications in VR
Sensing in VR
Multisensory feedbacks
computation
Naturalness of the interaction
Global gait
parameters
V
=
S F + direct
measurements
S L
Accelerometers on pelvis
Control of the virtual camera [ 35 ] Treadmill versus overground walking in
VR [ 14 ]
Walk-in-place [ 34 ]
Synchronization with sound [ 13 ]
“Shake-your-head” [ 36 ]
Curvature,
trajectory
Head, center of mass, feet
tracking
Could be used to improve camera
trajectory and galvanic
stimulation in nonlinear
walking
Comparison between walking paths in
real and in VR [ 35 ]
Balance status Center of pressure or zero
moment point (model)
Use of balance boards or
pressure plates
Joyman [ 19 , 26 ] interface
based on balance status
Asymmetry
and
regularity
Autocorrelation or
( R L )
0 . 5
Asymmetry could be related to
turning and could be used in
walk-in-place interfaces
Could be used to adjust camera
motion to the user's real-time
performance
Criteria used to evaluate the cognitive
load when walking [ 17 ]
×
100 R (resp. L): right
(resp. left) parameters
× ( R + L )
Joint angles
Direct evaluation or
kinematic model fitting
To improve walk-in-place
interfaces when
avoiding/stepping up
obstacles
Real-time animation of avatars
Comparison to reference data &
Individual trajectories
Joint torques
and forces
Inverse dynamics
Vibration feedbacks according to
the shape of the ground
reaction force [ 37 ]
Comparison to reference values; used to
evaluate treadmill walking in VR [ 14 ]
Muscle
activation
pattern
EMG + signal processing
or musculoskeletal
models
EMG to monitor the user's
actions
Real-time feedback of the user's
muscle coordination for
rehabilitation in VR
Comparison to reference values; used to
evaluate treadmill walking in VR [ 14 ]
 
 
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