what changes would you recommend

I am trying to do muscle fatigue analysis this is how far i have made. What changes i should make so that my code works.

for the acquired data set.

% 2 sec Time Trials
clear
clc
close all

files = dir('*.txt');     % Returns all the files and folders in the directory
fileTable = struct2table(files);
numOfFiles = height(fileTable);

for k = 1:numOfFiles % check for time trial files and excludes MVIC
    if strfind(fileTable.name{k}, 'sec')
        secfiles{k} = fileTable.name{k};
    end
end
allsecfiles = secfiles(:,~cellfun(@isempty,secfiles(1,:)));
masterData = struct;
for j = 1:length(allsecfiles) % compile file name information
    file_info(:,j) = split(allsecfiles(j), "_"); 
    masterData(j).group = file_info(1,j);
    masterData(j).time = file_info(2,j);
    masterData(j).trial = extractBefore(file_info(4,j),'.');
end

timetrials = {'2sec';'5sec';'10sec'}; % define iterations/categories of files
newfig = 1; % beginning figure 
r=1;
for t = 1:length(timetrials) % iterate for each time duration
    timetrialfiles = find(strcmp(file_info(2,:),timetrials{t})); % index files that correspond to selected time duraiton
    gettimefiles = allsecfiles(timetrialfiles); % files that correspond to time duration
       for s = 1:length(gettimefiles) % iterate for each trial (2 or 3)
        for c = 1:2 % iterate for columns for bicep and tricep
            if c==1
                musc_c = 'Bicep'; % Bicep data located in first 8 columns
                timecol = 1;
                emgcol = 2;
            else
                musc_c = 'Tricep'; % Tricep data located in second 8 columns
                timecol = 9;
                emgcol = 10;
            end
            imptimetrials = readtable(char(gettimefiles(s)));
            time = table2array(imptimetrials(:,timecol));
            emg = table2array(imptimetrials(:,emgcol));
            figure(newfig)
            plot(time,emg,'b') % plot raw EMG data in blue
            hold on
% determine where to split concentric and eccentric data based on file name   
            idc = strfind(timetrials,'2sec');   
            idx = ~cellfun('isempty',idc);
            findidx = find(idx==1);
            if findidx == t
                cut = 1;
                endtime = 2;
            else
                idc = strfind(timetrials,'5sec');   
                idx = ~cellfun('isempty',idc);
                findidx = find(idx==1);
                if findidx == t
                    cut = 2.5;
                    endtime = 5;
                else
                    cut = 5;
                    endtime = 10;
                end
            end
            
            con = find(time < cut & time > 0); % first half of time trial
            ecc = find(time > cut & time < endtime);
            contime = time(con);
            conemg = emg(con);
            ecctime = time(ecc);
            eccemg = emg(ecc);
            figure(newfig)
            plot(contime,conemg, 'Color','#D95319') 
            hold on
            plot(ecctime,eccemg, 'Color','#EDB120') % plot second half in yellow
            xlabel('Time (s)')
            ylabel('EMG Response (mV)')
          
            legend(sprintf('%s EMG',musc_c), 'Concentric', 'Eccentric')
            title(sprintf('%s: %s EMG vs Time [Trial %d]',timetrials{t},musc_c,s))
            hold off
            newfig = newfig+1;

            figure(newfig)
% Plot Concentric Rectified            
            subplot(1,2,1)
            plot(contime,conemg,'b')
            hold on
            smooth_con = smooth(abs(conemg - mean(conemg)));
            plot(contime,smooth_con,'k')
            hold on 
            RMScon = sqrt(movmean(smooth_con.^2,500));
            plot(contime,RMScon,'r')
            legend('RawEMG','Rectified EMG','Moving Average')
            title(sprintf('%s %s EMG: Concentric Contraction vs Time',timetrials{t}, musc_c))
            xlabel('Time (s)')
            ylabel('EMG Response (mV)')
            hold off
% Plot Eccentric Rectified 
            subplot(1,2,2)
            plot(ecctime, eccemg, 'b')
            hold on
            smooth_ecc = smooth(abs(eccemg-mean(eccemg)));
            plot(ecctime, smooth_ecc,'k')
            hold on 
            RMSecc = sqrt(movmean(smooth_ecc.^2,500));
            plot(ecctime,RMSecc,'r')
            legend('RawEMG','Rectified EMG','Moving Average')
            title(sprintf('%s %s EMG: Eccentric Contraction vs Time',timetrials{t}, musc_c))
            xlabel('Time (s)')
            ylabel('EMG Response (mV)')
            hold off
            newfig = newfig+1;
%% Rectified and Integrated EMG
% Concentric
            figure(newfig)
            subplot(1,2,1)
            plot(contime,smooth_con,'k')
            hold on 
            intCon = cumtrapz(RMScon);
            yyaxis right
            plot(contime,intCon,'g')
            legend('Rectified EMG','Integrated EMG')
            title(sprintf('%s %s EMG: Concentric Contraction vs Time',timetrials{t},musc_c))
            xlabel('Time (s)')
            ylabel('EMG Response (mV-s)')
            yyaxis left 
            ylabel('EMG Response (mV)')
            hold off
% Eccentric
            subplot(1,2,2)
            plot(ecctime,smooth_ecc,'k')
            hold on 
            intEcc = cumtrapz(RMSecc);
            yyaxis right
            plot(ecctime, intEcc,'g')
            legend('Rectified EMG','Integrated EMG')
            title(sprintf('%s %s EMG: Eccentric Contraction vs Time',timetrials{t},musc_c))
            xlabel('Time (s)')
            ylabel('EMG Response (mV-s)')
            yyaxis left 
            ylabel('EMG Response (mV)')
            hold off
            newfig = newfig+1;

            maxRMScon(r,c) = max(RMScon);
            maxRMSecc(r,c) = max(RMSecc);
            maxINTcon(r,c) = max(intCon);
            maxINTecc(r,c) = max(intEcc);

            fourier_con = smooth_con.*1000;
            fourier_ecc = smooth_ecc.*1000;
            fs = 2000;
            tau = 1/fs;
            lenCon = length(fourier_con);
            lenEcc = length(fourier_ecc);
            fftCon = abs(fft(fourier_con));
            fftEcc = abs(fft(fourier_ecc));
            truncCon = fftCon(1:lenCon/2+1);
            truncEcc = fftEcc(1:lenEcc/2+1);
            truncCon(2:end-1) = truncCon(2:end-1).*2;
            truncEcc(2:end-1) = truncEcc(2:end-1).*2;
            fc = ((0:(lenCon/2))./lenCon).*fs;
            fe = ((0:(lenEcc/2))./lenEcc).*fs;
            freqrange = 20:10:500;
            for fr = 1:length(freqrange)-1
                freqcon = [];
                freqecc = [];
                freqcon(fr) = medfreq(truncCon(freqrange(fr):freqrange(fr+1)),fs);
                freqecc(fr) = medfreq(truncEcc(freqrange(fr):freqrange(fr+1)),fs);
            end
            [pMaxCon,pMaxConLocs] = max(freqcon);
            [pMaxEcc,pMaxEccLocs] = max(freqecc);
            figure(newfig)
            subplot(1,2,1)
            xline(pMaxCon, '--r','LineWidth',2);
            hold on
            plot(fc,truncCon,'b-o')
            hold on
            xlim([20 500])
            xlabel('Frequency (Hz)')
            ylabel('Power Spectrum')
            title(sprintf('%s %s EMG: Concentric Power Spectrum',timetrials{t},musc_c))
            legend(sprintf('Median f = %d Hz', pMaxCon),sprintf('Power: %s Concentric %s', musc_c, timetrials{t}))
            hold off
            subplot(1,2,2)
            xline(pMaxEcc, '--r','LineWidth',2);
            hold on
            plot(fe,truncEcc,'b-o')
            hold on
            xlim([20 500])
            xlabel('Frequency (Hz)')
            ylabel('Power Spectrum')
            title(sprintf('%s %s EMG: Eccentric Power Spectrum',timetrials{t},musc_c))
            legend(sprintf('Median f = %d Hz', pMaxEcc),sprintf('Power: %s Eccentric %s', musc_c, timetrials{t}))
            hold off
            newfig = newfig+1;
            for myfig = 1:newfig-1
                    saveas(myfig,sprintf('%s_Fig%d.png', musc_c, myfig))
            end
 
        end 
        r = r+1;
    end
end

Answer 1

[Abhinaya Kennedy]

Hi Manav,

The provided code lays a good foundation for muscle fatigue analysis. Here's how to enhance it:

• Data Format: Ensure your text files (".txt") match the expected format: time in the first column, followed by Bicep EMG (first 8 columns) and Tricep EMG (next 8 columns). Modify the code if your format differs.
• Phase Identification: Your code relies on filenames ("2sec", "5sec") for phase identification. If your filenames lack this convention, adjust the logic to identify phases based on markers within the data or additional filename information.
• Multiple Trials: The code assumes one trial per time duration. If you have multiple trials, adapt the loop structure to handle them separately (e.g., additional loop or conditional statements).