Package: remodnav
REMoDNaV - Robust Eye Movement Detection for Natural ViewingREMoDNaV is a velocity based eye movement event detection algorithm that is based on, but
extends the adaptive Nyström & Holmqvist algorithm (Nyström & Holmqvist, 2010).
It is built to be suitable for both static and dynamic stimulation, and is
capable of detecting saccades, post-saccadic oscillations, fixations, and smooth
pursuit events. REMoDNaV is especially suitable for data without a trial structure
and performs robustly on data with temporally varying noise level.SupportAll bugs, concerns and enhancement requests for this software can be submitted here:https://github.com/psychoinformatics-de/remodnavIf you have a problem or would like to ask a question about how to use REMoDNaV,
pleasesubmit a question to
NeuroStars.orgwith aremodnavtag.  NeuroStars.org is a platform similar to StackOverflow
but dedicated to neuroinformatics.Any previous REMoDNaV questions can be found here:http://neurostars.org/tags/remodnav/Installation via pipInstall the latest version ofremodnavfromPyPi. It is recommended to use
a dedicatedvirtualenv:# create and enter a new virtual environment (optional)
virtualenv --python=python3 ~/env/remodnav
. ~/env/remodnav/bin/activate

# install from PyPi
pip install remodnavExample usagerequired (positional) arguments:REMoDNaV is easiest to use from the command line.
To get REMoDNaV up and running, supply the following required information in a
command line call:infile: Data file with eye gaze recordings to process. The first two columns
in this file must contain x and y coordinates, while each line is a timepoint
(no header). The file is read with NumPy'srecfromcsvand may be compressed.
The columns are expected to be seperated by tabulators (\t).outfile: Output file name. This file will contain information on all detected
eye movement events in BIDS events.tsv format.px2deg: Factor to convert pixel coordinates to visual degrees, i.e. the visual
angle of a single pixel. Pixels are assumed to be square. This will typically be a
rather small value.Note: you can compute this factor fromscreensize,viewing distanceandscreen resolutionwith the following formula:degrees(atan2(.5 * screen_size, viewing_distance)) / (.5 * screen_resolution)sampling rate: Sampling rate of the data in Hertz. Only data with dense regular
sampling are supported.Exemplary command line call:remodnav "inputs/raw_eyegaze/sub-01/ses-movie/func/sub-01_ses-movie_task-movie_run-1_recording-eyegaze_physio.tsv.gz" \
  "sub-01/sub-01_task-movie_run-1_events.tsv" 0.0185581232561 1000.0optional parameters:REMoDNaV comes with many configurable parameters. These parameters have sensible default values,
but they can be changed by the user within the command line call.
Further descriptions of these parameters can be found in the correspondingpublication.ParameterUnitDescription--min-blink-durationsecmissing data windows shorter than this duration will not be considered fordilate nan--dilate-nansecduration for which to replace data by missing data markers on either side of a signal-loss window.--median-filter-lengthsecsmoothing median-filter size (for initial data chunking only).--savgol-lengthsecsize of Savitzky-Golay filter for noise reduction.--savgol-polyordpolynomial order of Savitzky-Golay filter for noise reduction.--max-veldeg/secmaximum velocity threshold, will issue warning if exceeded to inform about potentially inappropriate filter settings.--min-saccade_durationsecminimum duration of a saccade event candidate.--max-pso_durationsecmaximum duration of a post-saccadic oscillation (glissade) candidate.--min-fixation_durationsecminimum duration of a fixation event candidate.--min-pursuit_durationsecminimum duration of a pursuit event candidate.--min-intersaccade_durationsecno saccade detection is performed in windows shorter than twice this value, plus minimum saccade and PSO duration.--noise-factoradaptive saccade onset threshold velocity is the median absolute deviation of velocities in the window of interest, times this factor (peak velocity threshold is twice the onset velocity); increase for noisy data to reduce false positives (Nyström and Holmqvist, 2010, equivalent: 3.0).--velthresh-startvelocitydeg/secstart value for adaptive velocity threshold algorithm (Nyström and Holmqvist, 2010), should be larger than any conceivable minimum saccade velocity.--max-initial-saccade-freqHzmaximum saccade frequency for initial detection of major saccades, initial data chunking is stopped if this frequency is reached (should be smaller than an expected (natural) saccade frequency in a particular context).--saccade-context-window-lengthsecsize of a window centered on any velocity peak for adaptive determination of saccade velocity thresholds (for initial data chunking only).--lowpass-cutoff-freqHzcut-off frequency of a Butterworth low-pass filter applied to determine drift velocities in a pursuit event candidate.--pursuit-velthreshdeg/secfixed drift velocity threshold to distinguish periods of pursuit from periods of fixation.Thus, to change the default value of any parameter(s), it is sufficient to include the parameter(s) and
the desired value(s) into the command line call:remodnav "inputs/raw_eyegaze/sub-01/ses-movie/func/sub-01_ses-movie_task-movie_run-1_recording-eyegaze_physio.tsv.gz" \
"sub-01/sub-01_task-movie_run-1_events.tsv" 0.0185581232561 1000.0 --min-blink-duration 0.05CitationDar, A. H., Wagner, A. S. & Hanke, M. (2019).REMoDNaV: Robust Eye Movement Detection for Natural Viewing.bioRxiv. DOI:10.1101/619254(first two authors contributed equally)LicenseMIT/ExpatContributingContributions in the form of issue reports, bug fixes, feature extensions are always
welcome.ReferencesNyström, M., & Holmqvist, K. (2010).An adaptive algorithm for fixation, saccade, and
glissade detection in eyetracking data.
Behavior research methods, 42(1), 188-204. DOI:10.3758/BRM.42.1.188