Data Collected through touch-screens linked up to MATLAB. During a one year Master's of Science (MSc) in Research Methods, which focused on Quantitative Methods, setting-up experiments and programming, several experiments were run using a IIyama Prolite 1700 SB touch screen. Participants were required to execute very rapid pointing movements to targets on the touch screen. Because the pointing movements were very rapid, they were also difficult to control fully. The project focused on participants learning their own motor variability, therefore understanding how precise/inaccurate their rapid pointing movements were. The more the participants learned this, the more they were able to hit targets and avoid hitting penalties.

This is the IIyama Prolite 1700 SB touch screen.

This system was used in the University of Glasgow Master's of Science Dissertation project (overall the MSc was obtained and awarded with Distinction)

Information about the pointing movements was then obtained from each participant and used to create a model of their "optimal" performance. Below is a model of the performance of participant RD when no penalty was present (first graph). The Red area is the center of the target. RD should aim roughly for the center of the target. In the second graph the target area RD wants to hit has a large penalty next to it. RD is very precise, so "optimal" performance for RD is to hit the orange area, which is still relatively large. This will lead RD to avoid the large penalty and only rarely miss the target. 

Data Analysis of the pointing movements was then conducted using MATLAB. Data Visualization and modeling was also carried out on MATLAB.