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reference:ft_detect_movement [2018/08/23 14:43] (current)
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 +=====  FT_DETECT_MOVEMENT =====
 +
 +Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_detect_movement"​.
 +
 +<​html><​pre>​
 +  FT_SACCADE_DETECTION performs micro/​saccade detection on time series data
 +  over multiple trials
 + 
 +  Use as
 +    movement = ft_detect_movement(cfg,​ data)
 + 
 +  The input data should be organised in a structure as obtained from the
 +  <a href=/​reference/​ft_preprocessing><​font color=green>​FT_PREPROCESSING</​font></​a>​ function. The configuration depends on the type of
 +  computation that you want to perform.
 + 
 +  The configuration should contain:
 +   ​cfg.method ​  = different methods of detecting different movement types
 +                 '​velocity2D',​ Micro/​saccade detection based on Engbert R,
 +                    Kliegl R (2003) Vision Res 43:​1035-1045. The method
 +                    computes thresholds based on velocity changes from
 +                    eyetracker data (horizontal and vertical components).
 +                 '​clustering',​ Micro/​saccade detection based on
 +                    Otero-Millan et al., (2014) J Vis 14 (not implemented
 +                    yet)
 +    cfg.channel = Nx1 cell-array with selection of channels, see
 +                  <a href=/​reference/​ft_channelselection><​font color=green>​FT_CHANNELSELECTION</​font></​a>​ for details, (default = '​all'​)
 +    cfg.trials ​ = '​all'​ or a selection given as a 1xN vector (default = '​all'​)
 + 
 +  METHOD SPECIFIC OPTIONS AND DESCRIPTIONS
 + 
 +   ​VELOCITY2D
 +    VELOCITY2D detects micro/​saccades using a two-dimensional (2D) velocity
 +    space velocity. The vertical and the horizontal eyetracker time series
 +    (one eye) are transformed into velocities and microsaccades are
 +    indentified as "​outlier"​ eye movements that exceed a given velocity and
 +    duration threshold.
 +      cfg.velocity2D.kernel ​  = vector 1 x nsamples, kernel to compute velocity (default = [1 1 0 -1 -1].*(data.fsample/​6);​
 +      cfg.velocity2D.demean ​  = '​no'​ or '​yes',​ whether to apply centering correction (default = '​yes'​)
 +      cfg.velocity2D.mindur ​  = minimum microsaccade durantion in samples (default = 3);
 +      cfg.velocity2D.velthres = threshold for velocity outlier detection (default = 6);
 + 
 +  The output argument "​movement"​ is a Nx3 matrix. The first and second
 +  columns specify the begining and end samples of a movement period
 +  (saccade, joystic...),​ and the third column contains the peak
 +  velocity/​acceleration movement. This last thrid column will allow to
 +  convert movements into spike data representation,​ making the spike
 +  toolbox functions compatible (not implemented yet).
 + 
 +  To facilitate data-handling and distributed computing you can use
 +    cfg.inputfile ​  ​= ​ ...
 +    cfg.outputfile ​ =  ...
 +  If you specify one of these (or both) the input data will be read from a *.mat
 +  file on disk and/or the output data will be written to a *.mat file. These mat
 +  files should contain only a single variable, corresponding with the
 +  input/​output structure.
 + 
 +  See also FT_PLOT_MOVEMENT (not implemented yet)
 +</​pre></​html>​