Organising and Analysing Eye-Tracking Data
c(
person("Hayward", "Godwin", email = "hg102@soton.ac.uk",role = c("aut", "cre")),
person("Alexander", "Muhl-Richardson", role = c("ctb")))
A set of functions for organising and analysing datasets from
experiments run using 'Eyelink' eye-trackers. Organising functions help
to clean and prepare eye-tracking datasets for analysis, and mark up
key events such as display changes and responses made by participants.
Analysing functions help to create means for a wide range of standard
measures (such as 'mean fixation durations'), which can then be fed into
the appropriate statistical analyses and graphing packages as necessary.
Hayward Godwin [aut, cre],
Alexander Muhl-Richardson [ctb]

Open Source Ophthalmic Data Sets Curated for R
c(
person("Tjebo", "Heeren",
role = c("aut", "cre"),
email = "tjebo@gmx.de",
comment = c(ORCID = "0000-0001-5297-2301")),
person("Dun Jack", "Fu",
role = c("aut"),
comment = c(ORCID = "0000-0003-2852-6912")))
Open source data allows for reproducible research and helps advance
our knowledge. The purpose of this package is to collate open source
ophthalmic data sets curated for direct use. This is real life data of
people with intravitreal injections with anti-vascular endothelial growth
factor (anti-VEGF), due to age-related macular degeneration or diabetic
macular edema. Associated publications of the data sets:
Fu et al. (2020) <doi:10.1001/jamaophthalmol.2020.5044>,
Moraes et al (2020) <doi:10.1016/j.ophtha.2020.09.025>,
Fasler et al. (2019) <doi:10.1136/bmjopen-2018-027441>,
Arpa et al. (2020) <doi:10.1136/bjophthalmol-2020-317161>,
Kern et al. 2020, <doi:10.1038/s41433-020-1048-0>.

Import Gaze Data for EyeLink Eye Tracker
person(given = "Alexander",
family = "Pastukhov",
role = c("aut", "cre"),
email ="pastukhov.alexander@gmail.com",
comment = c(ORCID = "0000-0002-8738-8591"))
Import gaze data from  edf files generated by
the SR Research <https://www.sr-research.com/> EyeLink eye tracker. Gaze data,
both recorded events and samples, is imported per trial. The package allows to extract
events of interest, such as saccades, blinks, etc. as well as
recorded variables and custom events (areas of interest, triggers) into separate tables.
The package requires EDF API library that can be obtained at <https://www.sr-support.com/>.
dplyr, fs, Rcpp, stringr, tidyr, methods, ggplot2