Help creating RMS Window

Hello,

I am supposed to import data from 10 Excel files then filter, rectify and create a RMS window for the data, but I am stuck at the last step. I am not very good at MATLAB, but I believe that I am on the right track so far. Any help would be extremely appreciated. I included what I have so far; the commented section at the end is what I am supposed to work off of. I tried a similar loop like the ones prior but did not succeed. Thank you in advance!

clear all; clc

fileName ={'Gait_normal01.csv';'Gait_normal02.csv';'Gait_rightlimp01.csv';'Gait_rightlimp02.csv';'MVC_Extension01.csv';...

'MVC_Extension02.csv';'MVC_Flexion01.csv';'MVC_Flexion02.csv';'SitStand01.csv';'Squat01.csv'}

% read in Data

for i=1:10

EMGraw_data{i,1} =dlmread(fileName{i,1},',',5,2);

end

%filter

for i=1:10

i

for j=1:4

j

[B,A]=butter(2,[10/500 350/500],'bandpass');

EMGf{i,1}(:,j) = filtfilt(B,A,EMGraw_data{i,1}(:,j));

end

end

% rectify

for i=1:10

i

for j=1:4

j

EMGrec{i,1}(:,j) = abs(EMGf{i,1}(:,j));

end

end

% %Root mean square

% winlength = 299; %input 1-desired window length

% EMGrms=zeros(length(EMGrec)-winlength,1);

% for i=1:length(EMGrec)-winlength;

% win=EMGrec(i:i+winlength);

% EMGrms(i+(winlength+1)/2)=sqrt(sum(win.^2)/winlength);

% end

Answer 1

[Mathieu NOE]

hello

here some demo code FYI

% dummy data
n = 1000;
Fs = 100;
dt = 1/Fs;
t=(0:n-1)*dt;
y = max(0.707,abs(cos(t))+0.1*rand(size(t)));

buffer = Fs;  % 1 second buffer (size in samples)
overlap = round(0.5*Fs); % overlap (here 50 % of buffer size) (size in samples)

[t_rms,y_rms] = my_rms(t,y,buffer,overlap);

figure(1),
plot(t,y,t_rms,y_rms,'r-*');
legend('raw data','1 s rms');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [t_rms,x_rms] = my_rms(t,x,buffer,overlap)

%%%% main loop %%%%
m = length(x);
dt = mean(diff(t));
shift = buffer-overlap;    % nb of samples between 2 contiguous buffers  

    for ci=1:fix((m-buffer)/shift +1)
        start_index = 1+(ci-1)*shift;
        stop_index = min(start_index+ buffer-1,m);
        t_rms(ci) = dt*(start_index+stop_index)/2;  % time (centered in buffer)
        x_rms(ci) = sqrt(mean(x(start_index:stop_index).^2));
    end
   
    
end

[Mathieu NOE]

problem solved ?

[Mathieu NOE]

hello again

problem solved ?