Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_channelrepair”.

  FT_CHANNELREPAIR repairs bad or missing channels in the data by replacing them with the
  plain average of of all neighbours, by a weighted average of all neighbours, by an
  interpolation based on a surface Laplacian, or by spherical spline interpolating (see
  Perrin et al., 1989).
  Use as
    [interp] = ft_channelrepair(cfg, data)
  The configuration must contain
    cfg.method         = 'weighted', 'average', 'spline', 'slap' or 'nan' (default = 'weighted')
    cfg.badchannel     = cell-array, see FT_CHANNELSELECTION for details
    cfg.missingchannel = cell-array, see FT_CHANNELSELECTION for details
    cfg.neighbours     = neighbourhood structure, see also FT_PREPARE_NEIGHBOURS
    cfg.trials         = 'all' or a selection given as a 1xN vector (default = 'all')
    cfg.lambda         = regularisation parameter (default = 1e-5, not for method 'distance')
    cfg.order          = order of the polynomial interpolation (default = 4, not for method 'distance')
  The weighted neighbour approach cannot be used reliably to repair multiple bad channels
  that lie next to each other.
  If you want to reconstruct channels that are absent in your data, those channels may
  also be missing from the sensor definition (grad, elec or opto) and determining the
  neighbours is non-trivial. In that case you must use a complete sensor definition from
  another dataset or from a template.
  The EEG, MEG or NIRS sensor positions can be present in the data or can be specified as
    cfg.elec          = structure with electrode positions, see FT_DATATYPE_SENS
    cfg.elecfile      = name of file containing the electrode positions, see FT_READ_SENS
    cfg.grad          = structure with gradiometer definition, see FT_DATATYPE_SENS
    cfg.gradfile      = name of file containing the gradiometer definition, see FT_READ_SENS
    cfg.opto          = structure with optode definition, see FT_DATATYPE_SENS
    cfg.optofile      = name of file containing the optode definition, see FT_READ_SENS
  This function only interpolates data over space, not over time. If you want to
  interpolate using temporal information, e.g. using a segment of data before and
  after the nan-marked artifact, you should use FT_INTERPOLATENAN.
  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.