diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m
index f8202c7..fb574f2 100644
--- a/usedMcode/callAll.m
+++ b/usedMcode/callAll.m
@@ -7,7 +7,7 @@
 noSynergies=3;
 
 allSubjects=true; %run all subjects and days or only one random day for one random subject
-name='default3Syn'; %suffix for the output, has to be valid name for file (no space, /, ...)
+name='EEGtoEMG'; %suffix for the output, has to be valid name for file (no space, /, ...)
 windowEMG=0.2;
 windowEEG=1;
 shiftEMG=0.05;
@@ -40,39 +40,41 @@
 
 if allSubjects
     
-    meanAccurancysEMG=zeros([j,1]);
-    meanAccurancysEEG=zeros([j,1]);
-    meanAccurancysLF=zeros([j,1]);
-    maxCEMG=zeros([j,k,1]);
-    maxCEEG=zeros([j,k,1]);
-    maxCLF=zeros([j,k,1]);
-    cmScaledEMG=zeros([j,5,5]);
-    cmScaledEEG=zeros([j,5,5]);
-    cmScaledLF=zeros([j,5,5]);
-    maxRidgeParamIndexEEGkin=zeros([j,3,k]);
-    maxRidgeParamIndexEMGkin=zeros([j,3,k]);
-    maxRidgeParamIndexLFkin=zeros([j,3,k]);
-    correlationEMGkin=zeros([j,3]); %x,y,angle
-    correlationEEGkin=zeros([j,3]);
-    correlationLFkin=zeros([j,3]);
-    maxRidgeParamIndexEEGautoenc=zeros([j,noSynergies,k]);
-    maxRidgeParamIndexEMGautoenc=zeros([j,noSynergies,k]);
-    maxRidgeParamIndexLFautoenc=zeros([j,noSynergies,k]);
-    correlationEMGautoenc=zeros([j,noSynergies]);
-    correlationEEGautoenc=zeros([j,noSynergies]);
-    correlationLFautoenc=zeros([j,noSynergies]);
-    maxRidgeParamIndexEEGpca=zeros([j,noSynergies,k]);
-    maxRidgeParamIndexEMGpca=zeros([j,noSynergies,k]);
-    maxRidgeParamIndexLFpca=zeros([j,noSynergies,k]);
-    correlationEMGpca=zeros([j,noSynergies]);
-    correlationEEGpca=zeros([j,noSynergies]);
-    correlationLFpca=zeros([j,noSynergies]);
-    maxRidgeParamIndexEEGnnmf=zeros([j,noSynergies,k]);
-    maxRidgeParamIndexEMGnnmf=zeros([j,noSynergies,k]);
-    maxRidgeParamIndexLFnnmf=zeros([j,noSynergies,k]);
-    correlationEMGnnmf=zeros([j,noSynergies]);
-    correlationEEGnnmf=zeros([j,noSynergies]);
-    correlationLFnnmf=zeros([j,noSynergies]);
+%     meanAccurancysEMG=zeros([j,1]);
+%     meanAccurancysEEG=zeros([j,1]);
+%     meanAccurancysLF=zeros([j,1]);
+%     maxCEMG=zeros([j,k,1]);
+%     maxCEEG=zeros([j,k,1]);
+%     maxCLF=zeros([j,k,1]);
+%     cmScaledEMG=zeros([j,5,5]);
+%     cmScaledEEG=zeros([j,5,5]);
+%     cmScaledLF=zeros([j,5,5]);
+%     maxRidgeParamIndexEEGkin=zeros([j,3,k]);
+%     maxRidgeParamIndexEMGkin=zeros([j,3,k]);
+%     maxRidgeParamIndexLFkin=zeros([j,3,k]);
+%     correlationEMGkin=zeros([j,3]); %x,y,angle
+%     correlationEEGkin=zeros([j,3]);
+%     correlationLFkin=zeros([j,3]);
+%     maxRidgeParamIndexEEGautoenc=zeros([j,noSynergies,k]);
+%     maxRidgeParamIndexEMGautoenc=zeros([j,noSynergies,k]);
+%     maxRidgeParamIndexLFautoenc=zeros([j,noSynergies,k]);
+%     correlationEMGautoenc=zeros([j,noSynergies]);
+%     correlationEEGautoenc=zeros([j,noSynergies]);
+%     correlationLFautoenc=zeros([j,noSynergies]);
+%     maxRidgeParamIndexEEGpca=zeros([j,noSynergies,k]);
+%     maxRidgeParamIndexEMGpca=zeros([j,noSynergies,k]);
+%     maxRidgeParamIndexLFpca=zeros([j,noSynergies,k]);
+%     correlationEMGpca=zeros([j,noSynergies]);
+%     correlationEEGpca=zeros([j,noSynergies]);
+%     correlationLFpca=zeros([j,noSynergies]);
+%     maxRidgeParamIndexEEGnnmf=zeros([j,noSynergies,k]);
+%     maxRidgeParamIndexEMGnnmf=zeros([j,noSynergies,k]);
+%     maxRidgeParamIndexLFnnmf=zeros([j,noSynergies,k]);
+%     correlationEMGnnmf=zeros([j,noSynergies]);
+%     correlationEEGnnmf=zeros([j,noSynergies]);
+%     correlationLFnnmf=zeros([j,noSynergies]);
+    maxRidgeParamIndexEEGemg=zeros([j,noSynergies,k]);
+    correlationEMGemg=zeros([j,noSynergies]);
     
     parfor j=1:size(numbersMat,2)
         number=numbersMat(j);
@@ -93,6 +95,7 @@
         [correlationEMGnnmf(j,:),maxRidgeParamIndexEMGnnmf(j,:,:)]=ridgeCV(savePath,'EMG','NNMF',k,ridgeParams,eegOffset);
         [correlationEEGnnmf(j,:),maxRidgeParamIndexEEGnnmf(j,:,:)]=ridgeCV(savePath,'EEG','NNMF',k,ridgeParams,eegOffset);
         [correlationLFnnmf(j,:),maxRidgeParamIndexLFnnmf(j,:,:)]=ridgeCV(savePath,'LF','NNMF',k,ridgeParams,eegOffset);
+        [correlationEEGemg(j,:),maxRidgeParamIndexEEGemg(j,:,:)]=ridgeCV(savePath,'EEG','EMG',k,ridgeParams,eegOffset);
         fprintf('%s%i finished %s\n',subject,number,datestr(datetime('now')))
     end
     
@@ -103,21 +106,22 @@
     number=numbersMat(j);
     subject=subjectsForNumbers{j};
     savePath=readAll(pathToFile,subject,number,windowEMG,windowEEG,shiftEMG,shiftEEG,maxFile,threshold,pburgOrder,minEEGFreq,maxEEGFreq,pause,noLFsamples,EMGChannels,noSynergies);
-    [meanAccurancysEMG,maxCEMG,cmScaledEMG(:,:)]=svmEciton(savePath,'EMG',k,maxExpC,maxPerClass,eegOffset);
-    [meanAccurancysEEG,maxCEEG,cmScaledEEG(:,:)]=svmEciton(savePath,'EEG',k,maxExpC,maxPerClass,eegOffset);
-    [meanAccurancysLF,maxCLF,cmScaledLF(:,:)]=svmEciton(savePath,'LF',k,maxExpC,maxPerClass,eegOffset);
-    [correlationEMGkin,maxRidgeParamIndexEMGkin(:,:)]=ridgeCV(savePath,'EMG','kin',k,ridgeParams,eegOffset);
-    [correlationEEGkin,maxRidgeParamIndexEEGkin(:,:)]=ridgeCV(savePath,'EEG','kin',k,ridgeParams,eegOffset);
-    [correlationLFkin,maxRidgeParamIndexLFkin(:,:)]=ridgeCV(savePath,'LF','kin',k,ridgeParams,eegOffset);
-    [correlationEMGautoenc,maxRidgeParamIndexEMGautoenc(:,:)]=ridgeCV(savePath,'EMG','Autoenc',k,ridgeParams,eegOffset);
-    [correlationEEGautoenc,maxRidgeParamIndexEEGautoenc(:,:)]=ridgeCV(savePath,'EEG','Autoenc',k,ridgeParams,eegOffset);
-    [correlationLFautoenc,maxRidgeParamIndexLFautoenc(:,:)]=ridgeCV(savePath,'LF','Autoenc',k,ridgeParams,eegOffset);
-    [correlationEMGpca,maxRidgeParamIndexEMGpca(:,:)]=ridgeCV(savePath,'EMG','PCA',k,ridgeParams,eegOffset);
-    [correlationEEGpca,maxRidgeParamIndexEEGpca(:,:)]=ridgeCV(savePath,'EEG','PCA',k,ridgeParams,eegOffset);
-    [correlationLFpca,maxRidgeParamIndexLFpca(:,:)]=ridgeCV(savePath,'LF','PCA',k,ridgeParams,eegOffset);
-    [correlationEMGnnmf,maxRidgeParamIndexEMGnnmf(:,:)]=ridgeCV(savePath,'EMG','NNMF',k,ridgeParams,eegOffset);
-    [correlationEEGnnmf,maxRidgeParamIndexEEGnnmf(:,:)]=ridgeCV(savePath,'EEG','NNMF',k,ridgeParams,eegOffset);
-    [correlationLFnnmf,maxRidgeParamIndexLFnnmf(:,:)]=ridgeCV(savePath,'LF','NNMF',k,ridgeParams,eegOffset);
+%     [meanAccurancysEMG,maxCEMG,cmScaledEMG(:,:)]=svmEciton(savePath,'EMG',k,maxExpC,maxPerClass,eegOffset);
+%     [meanAccurancysEEG,maxCEEG,cmScaledEEG(:,:)]=svmEciton(savePath,'EEG',k,maxExpC,maxPerClass,eegOffset);
+%     [meanAccurancysLF,maxCLF,cmScaledLF(:,:)]=svmEciton(savePath,'LF',k,maxExpC,maxPerClass,eegOffset);
+%     [correlationEMGkin,maxRidgeParamIndexEMGkin(:,:)]=ridgeCV(savePath,'EMG','kin',k,ridgeParams,eegOffset);
+%     [correlationEEGkin,maxRidgeParamIndexEEGkin(:,:)]=ridgeCV(savePath,'EEG','kin',k,ridgeParams,eegOffset);
+%     [correlationLFkin,maxRidgeParamIndexLFkin(:,:)]=ridgeCV(savePath,'LF','kin',k,ridgeParams,eegOffset);
+%     [correlationEMGautoenc,maxRidgeParamIndexEMGautoenc(:,:)]=ridgeCV(savePath,'EMG','Autoenc',k,ridgeParams,eegOffset);
+%     [correlationEEGautoenc,maxRidgeParamIndexEEGautoenc(:,:)]=ridgeCV(savePath,'EEG','Autoenc',k,ridgeParams,eegOffset);
+%     [correlationLFautoenc,maxRidgeParamIndexLFautoenc(:,:)]=ridgeCV(savePath,'LF','Autoenc',k,ridgeParams,eegOffset);
+%     [correlationEMGpca,maxRidgeParamIndexEMGpca(:,:)]=ridgeCV(savePath,'EMG','PCA',k,ridgeParams,eegOffset);
+%     [correlationEEGpca,maxRidgeParamIndexEEGpca(:,:)]=ridgeCV(savePath,'EEG','PCA',k,ridgeParams,eegOffset);
+%     [correlationLFpca,maxRidgeParamIndexLFpca(:,:)]=ridgeCV(savePath,'LF','PCA',k,ridgeParams,eegOffset);
+%     [correlationEMGnnmf,maxRidgeParamIndexEMGnnmf(:,:)]=ridgeCV(savePath,'EMG','NNMF',k,ridgeParams,eegOffset);
+%     [correlationEEGnnmf,maxRidgeParamIndexEEGnnmf(:,:)]=ridgeCV(savePath,'EEG','NNMF',k,ridgeParams,eegOffset);
+%     [correlationLFnnmf,maxRidgeParamIndexLFnnmf(:,:)]=ridgeCV(savePath,'LF','NNMF',k,ridgeParams,eegOffset);
+    [correlationEEGemg,maxRidgeParamIndexEEGemg(:,:)]=ridgeCV(savePath,'EEG','EMG',k,ridgeParams,eegOffset);
     fprintf('%s%i finished %s\n',subject,number,datestr(datetime('now')))
     
     save(strcat(pathToFile,sprintf('../matlabData/%s_call%s%i-%s.mat',datestr(datetime('now')),subject,number,name)));
diff --git a/usedMcode/generateTrainingData.m b/usedMcode/generateTrainingData.m
index 8637129..5409540 100644
--- a/usedMcode/generateTrainingData.m
+++ b/usedMcode/generateTrainingData.m
@@ -4,7 +4,8 @@
     tempEEG=zeros([32,fix(floor(size(signal,1)/signalWindowEEG-1)*windowEEG/shiftEEG+1),201]);
     tempEEGlf=zeros([32,fix(floor(size(signal,1)/signalWindowEEG-1)*windowEEG/shiftEEG+1),noLFsamples]);
     
-    %Filter around 50Hz and below 2 Hz
+    %Filter around 50 Hz and 150 Hz
+    % filter for the range minEEGFreq to maxEEGFreq
     [A,B]= butter(2,[48 52]/(bci_sf/2),'stop');
     [C,D]= butter(2,minEEGFreq/(bci_sf/2),'high');
     [E,F]= butter(2,[148 152]/(bci_sf/2),'stop');
diff --git a/usedMcode/ridgeCV.m b/usedMcode/ridgeCV.m
index a4a1ff4..403ff76 100644
--- a/usedMcode/ridgeCV.m
+++ b/usedMcode/ridgeCV.m
@@ -28,8 +28,10 @@
         predicted=shiftingMean(synergiesNNMF,factor);
     elseif strcmp(goal,'kin')
         predicted=shiftingMean(kinematics,factor);
+    elseif strcmp(data,'EMG')
+        predicted=trainingDataEMG;
     else
-        error('only kin, Autoenc, PCA and NNMF are valid inputs for goal');
+        error('only kin, Autoenc, PCA, NNMF and EMG are valid inputs for goal');
     end
 
     clear kinematics;