NadicaSm/Sensing-Time-Calculation-from-the-Eye-Tracker-Videos:

This repository contains Python code for calculation of the sensing time (ST) parameters from the eye-tracker videos that is available on GitHub repository - https://github.com/NadicaSm/Sensing-Time-Calculation-from-the-Eye-Tracker-Videos. This is a supplementary material for the preprint available on arXiv and titled "Sensing Time Effectiveness for Fitness to Drive Evaluation in Neurological Patients" authored by Nadica Miljković and Jaka Sodnik . 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. (2022). NadicaSm/Sensing-Time-Calculation-from-the-Eye-Tracker-Videos (v1.0.0). [Software code], Zenodo. https://doi.org/10.5281/zenodo.6560419 Miljković, N., & Sodnik, J. (2022, May). Sensing Time Effectiveness for Fitness to Drive Evaluation in Neurological Patients. Preprint in arXiv (pp. 1-23). https://doi.org/10.48550/arXiv.2205.08942 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 sensing time parameter.FUNDING: N.M. acknowledges amiable support from the Grant No. 451-03-68/2022-14/200103 funded by the Ministry of Education, Science, and Technological Development, 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