diff --git a/.gitignore b/.gitignore
index e7fb459..f84bf05 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,7 +7,7 @@
 src/
 matlabData/
 *mex*
-Block*
+origData/
 BCI2000*
 *.mat
 *.zip
diff --git a/oldMcode/correlation2.m b/oldMcode/correlation2.m
deleted file mode 100644
index ce92014..0000000
--- a/oldMcode/correlation2.m
+++ /dev/null
@@ -1,9 +0,0 @@
-function [R2]=correlation2(A,B)
-    if size(A)~=size(B)
-        error('dimension missmatch')
-    end
-    R2=zeros(size(A,2),1);
-    for i=1:size(A,2)
-        R2(i)=corr(A(:,i),B(:,i))^2;
-    end
-end
\ No newline at end of file
diff --git a/oldMcode/noOfSynergies.m b/oldMcode/noOfSynergies.m
deleted file mode 100644
index f752137..0000000
--- a/oldMcode/noOfSynergies.m
+++ /dev/null
@@ -1,42 +0,0 @@
-maxSize=min(6,size(trainingData,2));
-
-r2Autoenc=zeros([maxSize,size(trainingData,2)]);
-for i=1:maxSize
-    ae=trainAutoencoder(trainingData,i,'ShowProgressWindow',false);
-    predicted=predict(ae,trainingData);
-    r2Autoenc(i,:)=correlation2(trainingData,predicted);
-end
-
-fig=figure();
-subplot(1,3,1);
-plot(r2Autoenc)
-title('Autoencoder')
-xlabel('number of syergies')
-ylabel('R^2')
-
-%PCA
-[COEFF,SCORE,latent] = pca(trainingData,'Centered',false);
-r2PCA=zeros([maxSize,size(trainingData,2)]);
-for i=1:maxSize
-    predicted=SCORE(:,1:i)*COEFF(:,1:i)';
-    r2PCA(i,:)=correlation2(trainingData,predicted);   
-end
-subplot(1,3,2);
-plot(r2PCA)
-title('PCA')
-xlabel('number of syergies')
-ylabel('R^2')
-
-%NNMF
-r2NNMF=zeros([maxSize,size(trainingData,2)]);
-for i=1:maxSize
-    [W,H]=nnmf(trainingData,i);
-    predicted=W*H;
-    r2NNMF(i,:)=correlation2(trainingData,predicted);
-end
-
-subplot(1,3,3);
-plot(r2NNMF)
-title('NNMF')
-xlabel('number of syergies')
-ylabel('R^2')
\ No newline at end of file
diff --git a/usedMcode/correlation2.m b/usedMcode/correlation2.m
new file mode 100644
index 0000000..db4b233
--- /dev/null
+++ b/usedMcode/correlation2.m
@@ -0,0 +1,9 @@
+function [R2]=correlation2(A,B)
+    if size(A)~=size(B)
+        error('dimension missmatch')
+    end
+    R2=zeros(size(A,2),1);
+    for i=1:size(A,2)
+        R2(i)=corr(A(:,i),B(:,i)).^2;
+    end
+end
\ No newline at end of file
diff --git a/usedMcode/noOfSynergies.m b/usedMcode/noOfSynergies.m
new file mode 100644
index 0000000..e440cdb
--- /dev/null
+++ b/usedMcode/noOfSynergies.m
@@ -0,0 +1,72 @@
+addpath('/home/hohlochj/masterarbeit/usedMcode')
+pathToFile='/nfs/wsi/ti/messor/hohlochj/origData/';
+%pathToFile='/home/jph/Uni/masterarbeit/origData/';
+maxFile=5;
+
+[subjects,numbers]=namesAndNumbers(pathToFile);
+numbersMat=cell2mat(numbers);
+subjectsForNumbers=cell(size(numbersMat,2),1);
+j=1;
+for i=1:size(subjects,2)
+    subject=subjects{i};
+    for number=numbers{i}
+        subjectsForNumbers{j}=subject;
+        j=j+1;
+    end
+end
+j=j-1;
+
+EMG=cell(size(numbersMat,2),1);
+
+parfor j=1:size(numbersMat,2)
+    number=numbersMat(j);
+    subject=subjectsForNumbers{j};
+    EMG{j}=readEMGSig(pathToFile,subject,number,maxFile);
+end
+
+trainingData=cell2mat(EMG);
+
+
+
+maxSize=6;
+
+r2Autoenc=zeros([maxSize,size(trainingData,2)]);
+for i=1:maxSize
+    ae=trainAutoencoder(trainingData',i,'ShowProgressWindow',false);
+    predicted=predict(ae,trainingData');
+    r2Autoenc(i,:)=correlation2(trainingData,predicted');
+end
+
+fig=figure();
+subplot(1,3,1);
+plot(r2Autoenc)
+title('Autoencoder')
+xlabel('number of syergies')
+ylabel('R^2')
+
+%PCA
+[COEFF,SCORE,latent] = pca(trainingData,'Centered',false);
+r2PCA=zeros([maxSize,size(trainingData,2)]);
+for i=1:maxSize
+    predicted=SCORE(:,1:i)*COEFF(:,1:i)';
+    r2PCA(i,:)=correlation2(trainingData,predicted);   
+end
+subplot(1,3,2);
+plot(r2PCA)
+title('PCA')
+xlabel('number of syergies')
+ylabel('R^2')
+
+%NNMF
+r2NNMF=zeros([maxSize,size(trainingData,2)]);
+for i=1:maxSize
+    [W,H]=nnmf(trainingData,i);
+    predicted=W*H;
+    r2NNMF(i,:)=correlation2(trainingData,predicted);
+end
+
+subplot(1,3,3);
+plot(r2NNMF)
+title('NNMF')
+xlabel('number of syergies')
+ylabel('R^2')
\ No newline at end of file
diff --git a/usedMcode/readEMGSig.m b/usedMcode/readEMGSig.m
new file mode 100644
index 0000000..f03da3a
--- /dev/null
+++ b/usedMcode/readEMGSig.m
@@ -0,0 +1,11 @@
+function [EMG]=readEMGSig(pathToFile,subject,number,maxFile)
+    EMGcell=cell(maxFile,1);
+    usedChannels={'AbdPolLo','Biceps','Triceps','FrontDelt','MidDelt','BackDelt'};
+    
+    for i=1:maxFile
+        [sig, ~, params] = load_bcidat(strcat(pathToFile,sprintf('%s/%s_B100%i/%s_B1S00%iR0%i.dat',subject,subject,number,subject,number,i)));
+        EMGcell{i}=sig(:,ismember(params.ChannelNames.Value,usedChannels));
+    end
+    
+    EMG=cell2mat(EMGcell);
+end
\ No newline at end of file