Platform for trajectory tracking experiments & data analysis
TrajTracker Analyze: Features
Preprocessing
TrajTracker Analyze expects the data format exported from TrajTracker Experiment paradigms.
It will preprocess the data, including:

Convert the data into easytouse matlab structures.

Resample the trajectory data into a fixed sampling rate, for easier analysis

Smooth the trajectory data

Calculate several measures per time point along the trajectory: direction, implied endpoints, speed, acceleration.

A set of perlbased scripts to easily handle the raw data files (filter, copy/move)

... and more
Visualization
TrajTracker Analyze supports several kinds of plots for basic visualization of the data, e.g.:

Averagetrajectories per target number: geometrical plots (x coord by y coord), temporal plots (x coordinate by time), momentaryfingerdirection plots.

Singletrial raw trajectories

Show any data per time point
Regressions
TrajTracker Analyze has a powerful mechanism for analyzing the data with regressions.

Regressions can be run per trial or per timepoint within the trajectory.

Extremely easy definition of new regression models.

The dependent variable and the predictors can be set to a large variety of predefined measures  pertrial measures (e.g., the target number, the movement time) and withintrajectory measures (e.g., momentary coordinates or speed).

Userdefined measures can be easily plugged into the regression model


Several grouplevel analyses of regression results (significance of predictors, comparison between predictors)

Highly configurable plots of the regression results.
Other analyses
For example,

Look for acceleration/deceleration points to detect changes of mind.

Calculate the firstfingerdeviation time as an index for the time when the stimulus information became available.

Parse each trajectory into a sequence of clockwise and counterclockwise curves, and extract several types of information about these curves