Hello, I’m currently trying to create a research project in which I use Core to track gaze fixation on a golf ball. I’m still playing around in the software, but I’m having problems in getting the program to identify a golf ball while its moving. Is this possible or do fixation durations have to be on stationary objects? Any help would be greatly appreciated.

Hi @user-0a22da! Let's move this to the 👁 core channel! I'll post an answer there!

My experiment looks at the effects of sensory feedback on eye movements during slot machine play. We had participants wear the eye-tracker (with recording from right eye only) and play for about 20 minutes. Our sample size is around 156 participants. We have looked at about 1/3rd of the video files to see what can be salvaged. Since we are only interested in the eye movements on the surface of the slot machine screen, I am making sure the video files are intact (i.e. looking for consistent pick-up of fixations and a complete video that was properly calibrated). Our basic sense/decision is to not use files where the world video does not capture the whole screen, their were issues with calibration (based on RA notes and lack of marker during offline processing of surface data), the visualized data looks somewhat shifted/skewed visibly, or if recording was done in a single session. What do people think about our decisions? There seems to be no way to salvage incorrectly calibrated data or use data where half the screen is missing.

Just to add on, we are dividing our surface into 4 sub-regions post-hoc: 1. reels, 2. credit window, 3. win window, and 4. others (anything else that does not fit into first 3 windows).