Biomedical Engineering Reference
In-Depth Information
be tuned according to biomechanical knowledge in order to enrich the variability and
commands when navigating in immersive environments. Data reported in this chap-
ter provide information for designing navigation systems that could adapt to gender,
age, size, and direction. Some authors have tried to implement such knowledge in
their controllers but it could be extended to more complex variations. Other types
of gait parameters have not been used yet such as EMG signals. Brain computer
interfaces use EEG signals coming from the brain to drive simulations in VR, but
we could imagine combining EEG and EMG to enhance the performance of the
classifiers in order to navigate in virtual environments. Such type of work has been
briefly addressed in biomechanics but might be relevant for VR applications.
Secondly, it can help to introduce multisensory feedback such as vibrations,
sounds, camera motion, etc., which should increase the naturalness of the navigation
task, as described in some recent papers. Adapting sound and vibrators' oscillations
to step length, frequency and weight, and to external parameters such as the type of
ground, is a promising issue. It has been explored in some recent papers and seems
to improve the quality of the navigation task in VR. In the same way, modifying
camera motions to avoid linear displacements which are not natural seems to be well
appreciated by users. Thanks to biomechanical knowledge it is possible to adapt
camera motions for many different parameters. For example, it would be possible
to recognize female and male camera motions. Indeed, it is well known that only a
few kinematic inputs enable people to recognize male and female gaits. Is it true for
camera motion?
Thirdly, it provides us with validation criterions that could help designers and
scientists evaluate the naturalness of navigation tasks in VR. Indeed, when navigating
in virtual environments the constraints of the real environment may disappear such
as trying to minimize metabolic energy, tiredness, jerk, etc. Moreover, interfaces,
such as using joysticks or pads, may lead to some binary commands. The resulting
trajectory could be composed of straight lines with few redirections which is very
different fromreal trajectories. Biomechanical knowledge reported in this chapter and
the related papers could help designers and scientists design a cost metrics function
to evaluate the performance of various navigation systems without requiring huge
experiments in real navigation tasks for comparison to their system.
References
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4. Alton F, Baldey L, Caplan S, Morrissey MC (1998) A kinematic comparison of overground
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