develop eye tracking insights
Gather open source implementations or write your own addons, e.g. for new eye tracking data format, event detection or drift correction algorithms.
Powerful visualizations with pyqtgraph.
Visualize raw data samples, fixations, saccades and blinks.
Due to the logging module, Eyeflow Studio will create reports about your analysis steps and your eye tracking data quality.
Automatically align Fixations with state of the art algorithms.
Correct for spatial drift on x- and y-axis on the basis of drift-checks in your experiment.
Inspect raw data and evaluate different event detection algorithms.
Batch-process data for multiple pages or subjects to speed up the process.
Visualize data as heatmaps and/or scan paths.
Adapt the visualization layout to your needs and preferences.
I am a researcher at the Unversity of Duisburg-Essen with a focus on eye tracking research, working with different eye tracking hardware and tasks that place high demands on the data, such as reading.
Most existing eye tracking analysis solutions are unsatisfactory for me - they often work with only one kind of hardware, do not include current research developments, like alternative event detection and fixation alignment algorithms; or do not offer flexible visualization to get a good insight into the data (quality).
So, I started to build my own program, to fill this gap.