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{{tag>example realtime}} ====== Example real-time average ====== ===== Flowchart ===== {{:example:realtime:realtime_average.png?350}} ===== Matlab code ===== <code matlab> function ft_realtime_average(cfg) % FT_REALTIME_AVERAGE is an example realtime application for online % averaging of the data. It should work both for EEG and MEG. % % Use as % ft_realtime_average(cfg) % with the following configuration options % = 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 % % To stop the realtime function, you have to press Ctrl-C % Copyright (C) 2009, Robert Oostenveld % % Subversion does not use the Log keyword, use 'svn log <filename>' or 'svn -v log | less' to get detailled information % set the default configuration options if ~isfield(cfg, 'dataformat'), cfg.dataformat = []; end % default is detected automatically if ~isfield(cfg, 'headerformat'), cfg.headerformat = []; end % default is detected automatically if ~isfield(cfg, 'eventformat'), cfg.eventformat = []; end % default is detected automatically if ~isfield(cfg, 'channel'), = 'all'; end if ~isfield(cfg, 'bufferdata'), cfg.bufferdata = 'last'; end % first or last % translate dataset into datafile+headerfile cfg = ft_checkconfig(cfg, 'dataset2files', 'yes'); cfg = ft_checkconfig(cfg, 'required', {'datafile' 'headerfile'}); % ensure that the persistent variables related to caching are cleared clear read_header % start by reading the header from the realtime buffer hdr = ft_read_header(cfg.headerfile, 'cache', true); % define a subset of channels for reading = channelselection(, hdr.label); chanindx = match_str(hdr.label,; nchan = length(chanindx); if nchan==0 error('no channels were selected'); end prevSample = 0; count = 0; % initialize the average, it will be filled on the first iteration avgsum = []; avgnum = []; % open a figure in which the average will be plotted figure %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % this is the general BCI loop where realtime incoming data is handled %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% while true % determine latest header and event information event = read_event(cfg.dataset, 'minsample', prevSample+1); % only consider events that are later than the data processed sofar hdr = read_header(cfg.dataset, 'cache', true); % the trialfun might want to use this, but it is not required cfg.event = event; % store it in the configuration, so that it can be passed on to the trialfun cfg.hdr = hdr; % store it in the configuration, so that it can be passed on to the trialfun % evaluate the trialfun, note that the trialfun should not re-read the events and header fprintf('evaluating ''%s'' based on %d events\n', cfg.trialfun, length(event)); trl = feval(cfg.trialfun, cfg); fprintf('processing %d trials\n', size(trl,1)); for trllop=1:size(trl,1) begsample = trl(trllop,1); endsample = trl(trllop,2); offset = trl(trllop,3); % remember up to where the data was read prevSample = endsample; count = count + 1; fprintf('processing segment %d from sample %d to %d\n', count, begsample, endsample); % read data segment from buffer dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', begsample, 'endsample', endsample, 'chanindx', chanindx, 'checkboundary', false); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % from here onward it is specific to the processing of the data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % apply some preprocessing options dat = preproc_baselinecorrect(dat); if isempty(average) % initialize the accumulating variables on the first call avgsum = dat; avgnum = 1; else avgsum = avgsum + dat; avgnum = avgnum + 1; end % compute the average avg = avgsum ./ avgnum; % create a time-axis and plot the average time = offset2time(offset, hdr.Fs, endsample-begsample+1); plot(time, avg); % force matlab to redraw the figure drawnow end % looping over new trials end % while true </code>