|
MouseTracker is a free-to-use, user-friendly software
package that allows researchers to measure real-time
hand movements from the streaming x, y
coordinates of the computer mouse (while behavioral
responses are made based on visual or auditory stimuli),
and subsequently visualize, process, and analyze them.
The software operates in a Windows XP/Vista/7
environment. It contains 3 programs:
1) Runner: a data collection program where a
researcher can specify stimuli files, timing, response options,
among other parameters, and run participants through studies
2) Designer: a graphics-based program to easily
set up the visual layout and response alternatives of an
experiment
3) Analyzer: a
graphics-based analysis
program can then import participants' data from such
studies and visualize, process, and analyze the mouse
movements.
The software
was designed with the intention of being
easy-to-use so that any researcher from any domain of
psychology or cognitive science (or beyond) could reap
the benefits of this new mouse-tracking technique for
her or his own research.
MouseTracker is able to handle
many different kinds of tasks (using images, letter
strings, and sounds--even sequentially or simultaneously) that
are uniquely customized by the researcher. As of version 2.0, an
unlimited number of response alternatives may be used, placed
anywhere on the screen. In terms of analysis,
the program can handle one individual participant's data or
aggregate across a whole group of participants' data at the same
time. MouseTracker automatically performs space-rescaling. Users
can select whether they want to conduct analyses in normalized
time or raw time. It easily groups mouse
trajectories by specified conditions and visualizes all
trajectories within specific conditions for side-by-side visual
comparisons. Trajectories can be explored and individually
selected for detailed information or exclusion. MouseTracker
generates mean trajectories of conditions and computes indices of spatial attraction/curvature and complexity. It also
conveniently z-normalizes these (both pooling across and
within conditions) for distributional analyses. It also can
generate velocity and acceleration profiles of trajectories. All
these data are then able to be exported into a
comma-separated-value (CSV) file for easy analyzing in Microsoft
Excel, prepared in a way that is basically ready-to-go for
hypothesis testing and (hopefully, if all went well!)
publication.
|
