Tools
In the lab, we have developed several tools for general use.
Titta: Interface to Tobii eye trackers using Tobii Pro SDK
• Matlab: https://github.com/dcnieho/Titta
• Python: https://github.com/marcus-nystrom/Titta
• Paper: Niehorster, D.C., Andersson, R. & Nyström, M. (2020). Titta: A toolbox for creating PsychToolbox and Psychopy experiments with Tobii eye trackers. Behavior Research Methods. doi: 10.3758/s13428-020-01358-8
SMITE: Interface to SMI eye trackers
• Matlab: https://github.com/dcnieho/SMITE
• Python: https://github.com/marcus-nystrom/SMITE
• Paper: Niehorster, D.C., & Nyström, M., (2019). SMITE: A toolbox for creating Psychtoolbox and Psychopy experiments with SMI eye trackers. Behavior Research Methods. doi: 10.3758/s13428-019-01226-0
GlassesViewer: Parser, viewer and coding GUI for eye movement data from Tobii Glasses 2 and 3
• Matlab: https://github.com/dcnieho/GlassesViewer
• Paper: Niehorster, D.C., Hessels, R.S., and Benjamins, J.S. (2020). GlassesViewer: Open-source software for viewing and analyzing data from the Tobii Pro Glasses 2 eye tracker. Behavior Research Methods. doi: 10.3758/s13428-019-01314-1
GlassesValidator: Tool for automatic determination of data quality (accuracy and precision) of wearable eye tracker recordings
• Python: https://github.com/dcnieho/glassesValidator
• Paper: Niehorster, D.C., Hessels, R.S., Benjamins, J.S., Nyström, M. and Hooge, I.T.C. (2023). GlassesValidator: A data quality tool for eye tracking glasses. Behavior Research Methods. doi: 10.3758/s13428-023-02105-5
I2MC: Noise-robust fixation classification for eye movement data
• Matlab: https://github.com/royhessels/I2MC
• Python: https://github.com/dcnieho/I2MC_Python
• Paper: Hessels, R.S., Niehorster, D.C., Kemner, C., & Hooge, I.T.C. (2017). Noise-robust fixation detection in eye-movement data - Identification by 2-means clustering (I2MC). Behavior Research Methods, 49(5): 1802--1823. doi: 10.3758/s13428-016-0822-1