Note that this reference documentation is identical to the help that is displayed in Matlab when you type “help ft_artifact_jump”.
FT_ARTIFACT_JUMP reads the data segments of interest from file and identifies SQUID jump artifacts. Use as [cfg, artifact] = ft_artifact_jump(cfg) with the configuration options cfg.dataset cfg.headerfile cfg.datafile Alternatively you can use it as [cfg, artifact] = ft_artifact_jump(cfg, data) In both cases the configuration should also contain cfg.trl = structure that defines the data segments of interest. See FT_DEFINETRIAL cfg.continuous = 'yes' or 'no' whether the file contains continuous data The data is preprocessed (again) with the following configuration parameters, which are optimal for identifying jump artifacts. cfg.artfctdef.jump.medianfilter = 'yes' cfg.artfctdef.jump.medianfiltord = 9 cfg.artfctdef.jump.absdiff = 'yes' Artifacts are identified by means of thresholding the z-transformed value of the preprocessed data. cfg.artfctdef.jump.channel = Nx1 cell-array with selection of channels, see FT_CHANNELSELECTION for details cfg.artfctdef.jump.cutoff = z-value at which to threshold (default = 20) cfg.artfctdef.jump.trlpadding = automatically determined based on the filter padding (cfg.padding) cfg.artfctdef.jump.artpadding = automatically determined based on the filter padding (cfg.padding) The output argument "artifact" is a Nx2 matrix comparable to the "trl" matrix of FT_DEFINETRIAL. The first column of which specifying the beginsamples of an artifact period, the second column contains the endsamples of the artifactperiods. To facilitate data-handling and distributed computing you can use cfg.inputfile = ... If you specify this option the input data will be read from a *.mat file on disk. This mat files should contain only a single variable named 'data', corresponding to the input structure. See also FT_REJECTARTIFACT, FT_ARTIFACT_CLIP, FT_ARTIFACT_ECG, FT_ARTIFACT_EOG, FT_ARTIFACT_JUMP, FT_ARTIFACT_MUSCLE, FT_ARTIFACT_THRESHOLD, FT_ARTIFACT_ZVALUE