NadicaSm/Time-To-Fixate-Calculation-from-the-Eye-Tracker-Videos: v2

This repository contains Python code for calculation of the time to fixate (TTF) parameters from the eye-tracker videos that is available on GitHub repository - https://github.com/NadicaSm/Time-To-Fixate-Calculation-from-the-Eye-Tracker-Videos. This is supplementary material for the paper titled "Effectiveness of a Time to Fixate for Fitness to Drive Evaluation in Neurological Patients" and authored by Nadica Miljković and Jaka Sodnik (published in Behavior Research Methods and previously shared on arXiv). Table with TTF parameters and other relevant features for 56 neurological patients and R code for statistical analysis are available on Zenodo repository: Miljković, N., & Sodnik, J. (2023). Parameters for Statistical Evaluation of Time to Fixate Effectiveness for Assessment of Fitness to Drive [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6560246 If you find these parameters and R code useful for your own research and teaching class, please cite the following references: Miljković, N., & Sodnik, J. (2023). NadicaSm/Time-To-Fixate-Calculation-from-the-Eye-Tracker-Videos: v2. [Software code], Zenodo. https://doi.org/10.5281/zenodo.6560419 Miljković, N., & Sodnik, J. (2023). Effectiveness of a time to fixate for fitness to drive evaluation in neurological patients. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02177-3 Motnikar, L., Stojmenova, K., Štaba, U. Č., Klun, T., Robida, K. R., & Sodnik, J. (2020). Exploring driving characteristics of fit-and unfit-to-drive neurological patients: A driving simulator study. Traffic Injury Prevention, 21(6), 359-364. https://doi.org/10.1080/15389588.2020.1764547 Acknowledgements J.S. kindly acknowledges University Rehabilitation Institute Soča employees and the Nervtech team. Authors gratefully appreciate the support from Nenad B. Popović, PhD from University of Belgrade – School of Electrical Engineering for his valuable assistance in design of illustrations and for provided feedback for the initial manuscript structure. Also, both Authors thank Nebojša Jovanović, MSc from University of Belgrade - School of Electrical Engineering for his kind contribution to earlier stages of the project, especially for his work on developing Python code to capture time to fixate parameter. Last but not least, we are very thankful to Damjan Krstajić, founder and director of the Research Centre for Cheminformatics for his precious advices on statistical analysis in a retrospective study and to student Gregor Kovač from Faculty of Electrical Engineering, University of Ljubljana for his diligent work on YOLO application in driving simulation.N.M. acknowledges amiable support from the Grant No. 451-03-47/2023-01/200103 funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia. This research was financially supported by Slovenian Research Agency within the research program ICT4QoL - Information and Communications Technologies for Quality of Life, grant number P2-0246, and the research project Neurophysiological and Cognitive Profiling of Driving Skills, grant number L2-8178