Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_realtime_classification”.
FT_REALTIME_CLASSIFICATION is an example realtime application for online classification of the data. It should work both for EEG and MEG. Use as ft_realtime_classification(cfg) with the following configuration options cfg.channel = cell-array, see FT_CHANNELSELECTION (default = 'all') cfg.trialfun = string with the trial function The source of the data is configured as cfg.dataset = string or alternatively to obtain more low-level control as cfg.datafile = string cfg.headerfile = string cfg.eventfile = string cfg.dataformat = string, default is determined automatic cfg.headerformat = string, default is determined automatic cfg.eventformat = string, default is determined automatic This function works with two-class data that is timelocked to a trigger. Data selection is based on events that should be present in the datastream or datafile. The user should specify a trial function that selects pieces of data to be classified, or pieces of data on which the classifier has to be trained.The trialfun should return segments in a trial definition (see FT_DEFINETRIAL). The 4th column of the trl matrix should contain the class label (number 1 or 2). The 5th colum of the trl matrix should contain a flag indicating whether it belongs to the test or to the training set (0 or 1 respectively). Example useage: cfg = ; cfg.dataset = 'Subject01.ds'; cfg.trialfun = 'trialfun_Subject01'; ft_realtime_classification(cfg); To stop the realtime function, you have to press Ctrl-C