%% Create an artificial set of QRS detections, based on multilead QRS detections.
% This is an auxiliar function for the ECGtask_QRS_detections_post_process.
% This function creates an artificial set of QRS detections, based on single
% lead detections, as described in [add reference].
%
% all_detections = wavedet_QRS_detection_mix(struct_in, ECG_header, start_end_this_segment )
%
% Arguments:
%
% + struct_in: the structure which results from loading the result of
% the QRS detection task used for invoking wavedet:
%
% cached_filenames = ECG_w.GetCahchedFileName('QRS_detection');
% struct_in = load(cached_filenames{1});
%
% +ECG_header: [struct] OPTIONAL.
%
% Description of the ECG typically available in the
% ECG_header. Structure with fields:
%
% -freq: Sampling rate in Hz. (1)
%
% -nsig: Number of ECG leads. (size(ECG,2))
%
% -nsamp: Number of ECG samples. (size(ECG,1))
%
% + start_end_this_segment: an array with the first and last sample
% indexes.
%
% Output:
%
% + all_detections: struct with the artificial detections named with
% prefix "wavedetMix_ECGmix".
%
% Example
%
% ECG_w.ECGtaskHandle = 'QRS_detections_post_process';
% % Mix QRS detections strategy function
% ECG_w.ECGtaskHandle.post_proc_func = 'calculate_artificial_QRS_detections';
% ECG_w.ECGtaskHandle.payload = load(cached_filenames{1});
% ECG_w.ECGtaskHandle.CalculatePerformance = true;
% ECG_w.Run;
%
% See also ECGtask_QRS_detections_post_process, wavedet_QRS_detection_mix
%
% Author: Mariano Llamedo Soria llamedom@electron.frba.utn.edu.ar
% Version: 0.1 beta
% Birthdate: 01/01/2014
% Last update: 14/07/2015
% Copyright 2008-2015
%
function all_detections = calculate_artificial_QRS_detections(struct_in, ECG_header, start_end_this_segment)
all_detections = [];
if( nargin < 3 || isempty(start_end_this_segment) )
start_end_this_segment = [1 ECG_header.nsamp];
end
% attemp to build a better detection from single-lead detections.
[~, all_annotations] = getAnnNames(struct_in);
[ ratios, estimated_labs ] = CalcRRserieRatio(all_annotations, ECG_header, start_end_this_segment);
[~, best_detections_idx] = sort(ratios, 'descend');
% generate artificial annotations combining K best annotations
aux_idx = best_detections_idx(1:min(10, length(best_detections_idx)) );
artificial_annotations = combine_anns(all_annotations(aux_idx), estimated_labs(aux_idx), ECG_header );
for ii = 1:length(artificial_annotations)
aux_str = ['mixartif_ECGmix' num2str(ii)];
all_detections.(aux_str) = artificial_annotations(ii);
end