Eliminate Outliers and filtering signal

I am using this code to apply different filters to my data from strain gages. How can I remove the outliers first, appy the filters and plot both signals? Do I need to use FFT ?

Thank you.

load('RRData.mat');

R=RRData.Strain_C_Fz;

L=RRData.Strain_HB_Fy;

t=RRData.Time;

samples = length(t);

Fs = (samples-1)/(t(samples)-t(1));

[R_max,idx]= max(R);

[L_max,idx]= max(L);

t_m = t(idx);

figure(1)

%subplot(3,2,1) ;

plot(t,R);hold on;plot(t,L);legend('Right','Left');

plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')

text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz' ]);

grid

% NB : decim = 1 will do nothing (output = input)

decim = 50;

if decim > 1

R = decimate (R,decim);

L = decimate (L,decim);

Fs = Fs/decim;

end

samples = length(R);

t = (0:samples - 1)*1/Fs;

[R_max,idx]= max(R);

[L_max,idx]= max(L);

t_m = t(idx);

figure(2)

%subplot(3,2,2) ;

plot(t,R); hold on; plot (t,L); legend('Right','Left');

plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')

text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz']);

grid on

figure(3)

N = 25;

Rs = slidingavg(R,N);

Ls = slidingavg(L,N);

[R_max,idx]= max(Rs);

[L_max,idx]= max(Ls);

t_m = t(idx);

%subplot(3,2,3) ;

plot(t,Rs); hold on; plot (t,Ls); legend('Right','Left');

plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')

text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz / Smoothed with slidingavg' ]);

grid on

figure(4)

N = 50;

Rs = medfilt1(R, N, 'truncate');

Ls = medfilt1(L, N, 'truncate');

[R_max,idx]= max(Rs);

[L_max,idx]= max(Ls);

t_m = t(idx);

%subplot(3,2,4) ;

plot(t,Rs); hold on; plot (t,Ls); legend('Right','Left');

plot(t_m, R_max,'^r');hold on; plot (t_m, L_max,'ro')

text(t_m,R(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', R_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

text(t_m,L(idx), sprintf('\\leftarrow Max = %.6f\n t = %.2f ', L_max,t_m), 'HorizontalAlignment','left', 'VerticalAlignment','top')

title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz / Smoothed with medfilt1' ]);

grid on

figure(5)

N = 50;

Rs = sgolayfilt(R,3,51);

Ls = sgolayfilt(L,3,51);

[Rs_max,index]= max(Rs);

[Ls_max,index]= max(Ls);

t_max = t(index);

%subplot(3,2,5) ;

plot(t,Rs); hold on; plot (t,Ls); legend('Right','Left');

plot(t_max, Rs_max,'^r');hold on; plot (t_max, Ls_max,'ro')

text(t_max,Rs(index),sprintf('\\leftarrow Max = %.6f\n t = %.2f ', Rs_max, t_max), 'HorizontalAlignment','left', 'VerticalAlignment','top')

text(t_max,Ls(index),sprintf('\\leftarrow Max = %.6f\n t = %.2f ', Ls_max, t_max), 'HorizontalAlignment','left', 'VerticalAlignment','top')

title(['Data samples at Fs = ' num2str(round(Fs)) 'Hz / Smoothed with sgolayfilt' ]);

grid on

Answer 1

[Chunru]

load RRData
% median filter to remove outliers (for 1 channel)
y1 = medfilt1(RRData.Strain_C_Fz, 7);
plot(RRData.Time, RRData.Strain_C_Fz, RRData.Time, y1)