Environmental Engineering Reference
In-Depth Information
analysis system connected to a Windows PC workstation. The VisualEyez system
monitors the 3-D positions of small infrared light emitting diodes (LEDs) located on
landmarks of interest. We typically utilize the tips of the thumb and index finger along
with the radial styloid at the wrist to demarcate the hand. Objects in the environment
are also equipped with three LEDs for motion tracking.
Once the motion information is obtained by the VisualEyez system, it is broadcast on a
subnetwork to a scene rendering Linux-based PC.
Using the motion capture information the scene is calculated and then rendered on a
downward facing CRT monitor, placed parallel to a work surface. A half-silvered
mirror is placed parallel to the computer monitor, midway between the screen and the
workspace. The image on the computer monitor is reflected in the mirror and is
perceived by subjects, wearing stereoscopic goggles, as if it were a three-dimensional
object located in the workspace below the mirror.
3.2 Human performance measurement
Human motor control, biomechanics and neuroscience research has provided a
comprehensive description of how humans reach to grasp and manipulate objects in natural
environments under a variety of sensory and environmental conditions (MacKenzie &
Iberall, 1994). By using the same measurement techniques as those employed to monitor
human performance in natural environments we can compare movement in virtual
environments to decades of existing human performance literature. The comparisons allow
the development of comprehensive cognitive models of human performance under various
sensory feedback conditions. Simple timing measures such as reaction time and movement
time provide a general description of upper limb movements. However, in motor control
studies, more complex three-dimensional kinematic measures such as displacement profiles,
movement velocity, deceleration time, and the formation of the grasp aperture (distance
between the index finger and thumb for a precision pinch grip) have also been used to
characterize object acquisition movements (MacKenzie & Iberall, 1994). By observing
regularities in the 3D kinematic information, inferences can be made regarding how
movements are planned and performed by the neuromotor control system. This detailed
movement information essentially provides a window into the motor control system and
allows the determination of what sensory feedback characteristics are important for
movement planning and production.
3.3 Preliminary experiments: Understanding vision for motor performance in virtual
environments across the lifespan
In a study investigating the role of visual feedback about the hand for the control of reach
to grasp movements, Mason and Bernardin (2009) demonstrated that young healthy
adults could utilize very simple visual feedback of their fingertips to improve motor
performance when compared to a condition in which no visual feedback of self was
present. The crude visual representation consisted of two 10 mm yellow spheres
representing the thumb and index finger tips (see Figure 2B for example). The visual
representation of the hand was always provided with moderate contrast. Mason and
Bernardin (2009) also noted that vision of the hand was not necessary throughout the
movement, but only up to movement onset. If vision of the hand was completely
