Eye-tracking - Start/stop recording on a trial basis or record the whole experiment?
Hi,
I'm both new to eye-tracking and to OpenSesame/PyGaze;
I've been looking into these tools for a few weeks now and at this point I have quite a few questions.
I'll start a few new discussions with some of these questions;
My apologies in advance if some of the questions are not very pertinent or if they are already answered elsewhere.
Any help will be much appreciated! Thanks! 
Regarding the current topic,
The eye-tracking template in OpenSesame starts and stops the recording of eye-tracking data once per trial; this is consistent with the PyGaze example scripts I found.
Other tools, such as Tobii Studio (I'm using a Tobii eye-tracker) seem to record the experiment continuously from start to finish.
Is it somehow ill-advised to use
pygaze_start_recording/pygaze_stop_recordingoutside the scope of a trial, to effectively record the whole experiment continuously?How would that relate to the need use
pygaze_drift_correct?Would that bring about any complications regarding the data analysis (I'll be looking into PyGaze Analyser and eyetrackingR for that).
The obvious downside of recording the whole experiment is generating more useless data; on the other hand, looking at the eye-tracking data, it seems that each time the eye-tracker starts recording there is a period of about 500 ms in which the tracking is not successful.
My congratulations and gratitude to Sebastiaan Mathôt and all the contributors to OpenSesame! It seems to be an amazing tool!
Best regards,
Bruno
Comments
Hi Bruno,
No, you can do that as well. This is more a way to indicate the trial-based structure (if any) of the experiment for later analysis.
The EyeLink cannot perform drift correction while recording. However, this may be different for other eye trackers, and I don't know in the case of a Tobii. I don't even know if the Tobii actually does drift correction. @Edwin?
But if the
pygaze_drift_correctitem throws an error, you will notice!That's a good question to ask yourself, because the way you set up your experiment can indeed make the analysis much easier or harder. But it's not a question that has a generally applicable answer.
I would first decide how you want to analyze your data, and look at the assumptions that this analysis procedure makes: how do you expect the data to be structured? How do you expect variables to be logged? Which messages do you expect? And then design your experiment with that in mind.
Cheers!
Sebastiaan
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Hi Sebastiaan,
Thank you for your reply and for the OpenSesame tool!