function [goodbeats,badbeats,outliers] = AnnotationConversion(annotations)
% [goodbeats,badbeats,outliers] = AnnotationConversion(annotations)
%
% OVERVIEW: Convert annotations to a logical array, with all Normal
% beats (labeled "N") returning as 1 and abnormal beats (not
% labeled "N") returning as 0.
%
% INPUT: annotations - a charactor array containing the annotations
% of heart beats, generated by GE MARS and then read by
% read_qrs.m
%
% OUTPUT: all outputs are returned in cell array format
% goodbeats - "N" beats
% badbeats - the logical inverse of goodbeats
% outliers - an array of points to be discarded when
% pre-processing the RR interval data.
% This includes not only bad beats, but the
% beats immediately following bad beats
%
% DEPENDENCIES & LIBRARIES:
% HRV_toolbox https://github.com/cliffordlab/hrv_toolbox
% WFDB Matlab toolbox https://github.com/ikarosilva/wfdb-app-toolbox
% WFDB Toolbox https://physionet.org/physiotools/wfdb.shtml
% REPO:
% https://github.com/cliffordlab/PhysioNet-Cardiovascular-Signal-Toolbox
% ORIGINAL SOURCE AND AUTHORS:
% Main script written by Adriana N. Vest
% Dependent scripts written by various authors
% (see functions for details)
% COPYRIGHT (C) 2016
% LICENSE:
% This software is offered freely and without warranty under
% the GNU (v3 or later) public license. See license file for
% more information
%%
goodbeats= strcmp(cellstr(annotations),'N'); % find good beats
badbeats = ~goodbeats; % badbeats is logical inverse of
% good beats
outliers = false(length(badbeats),1); % initialize vector to be use to
% eliminate bad beats
% removing beats after non-N beats
for i = 1:length(badbeats)
if badbeats(i)
outliers(i) = 1;
outliers(i+1) = 1;
end
end
% remove extra points that may have been introduced at the end of the file
if (length(outliers) > length(badbeats))
z = length(outliers);
outliers(z) = [];
end
end % end function