function [X]=preprocessing(tm,ecgs,gflag,nflag,bflag)
% preprocess ecg data
% gflag: flag indicating whether to fill the gaps
% nflat: flag indicating whether to reduce noise level
% bflag: flag indicating whether to remove baseline wandering
%
% Author: Xiaopeng Zhao
% Updated: Xiaopeng zhao, April 25, 2013
% =====================
% to do
% evaluate signal quality of each channel
X=ecgs;
N_chn=size(X,2); %num of channels
if gflag
% Use interpolation to fill the gaps in the data
ind_missing=isnan(ecgs);
% interpolation
for i=1:N_chn % for each channel
pos=ind_missing(:,i);
if sum(pos)~=0
X(pos,i)=interp1(tm(pos==0),ecgs(pos==0,i),tm(pos),'spline');
end
end
end
if nflag
% low-pass filter using 18-point moving average to suppress high frequency
% noise
M=9;
for i=1:N_chn
%X(:,i)=movAvg(X(:,i),2*M+1);
X(:,i)=smooth(X(:,i),2*M+1,'moving');
end
end
if bflag
% high-pass filter using 401 point moving average to suppress baseline
% wandering
% the smoothing function performs better than the movAvg function in
% tracing the baseline
M=200; %num of points for moving average
for i=1:N_chn
%tmp=movAvg(X(:,i),2*M+1);
tmp=smooth(X(:,i),2*M+1,'moving');
X(:,i)=X(:,i)-tmp;
end
end
% finally, we normlize the data to zero mean and std = 1
[X,Xs]=mapminmax(X');
X=X';
% X=mapstd(X')';
end