diff --git a/bashscripts/runOnEciton.bash b/bashscripts/runOnEciton.bash
index e6e6698..bf22f51 100755
--- a/bashscripts/runOnEciton.bash
+++ b/bashscripts/runOnEciton.bash
@@ -7,4 +7,4 @@
 #sed 's,\./,,g' -i dirs.txt
 #sed '/^[[:blank:]]*$/d' -i dirs.txt 
 
-matlab < /home/hohlochj/masterarbeit/usedMcode/callAll.m > /nfs/wsi/ti/messor/hohlochj/log/$(date +%y-%m-%d--%T)-EEGtoEMGandAutoencToKinAndVia.log
+matlab < /home/hohlochj/masterarbeit/usedMcode/callAll.m > /nfs/wsi/ti/messor/hohlochj/log/$(date +%y-%m-%d--%T)-MoveRest.log
diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m
index 1ea8bd8..dcd1ff9 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='EEGtoEMGandAutoencToKinandVia'; %suffix for the output, has to be valid name for file (no space, /, ...)
+name='MoveRest'; %suffix for the output, has to be valid name for file (no space, /, ...)
 windowEMG=0.2;
 windowEEG=1;
 shiftEMG=0.05;
@@ -22,7 +22,7 @@
 k=10;
 maxExpC=0;
 maxPerClass=250;
-poolObj=parpool(32);
+poolObj=parpool(12);
 
 [subjects,numbers]=namesAndNumbers(pathToFile);
 numbersMat=cell2mat(numbers);
@@ -40,12 +40,12 @@
 
 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]);
+     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]);
@@ -89,9 +89,9 @@
         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(j),maxCEMG(j,:),cmScaledEMG(j,:,:)]=svmEciton(savePath,'EMG',k,maxExpC,maxPerClass,eegOffset,true);
-%         [meanAccurancysEEG(j),maxCEEG(j,:),cmScaledEEG(j,:,:)]=svmEciton(savePath,'EEG',k,maxExpC,maxPerClass,eegOffset,true);
-%         [meanAccurancysLF(j),maxCLF(j,:),cmScaledLF(j,:,:)]=svmEciton(savePath,'LF',k,maxExpC,maxPerClass,eegOffset,true);
+         [meanAccurancysEMG(j),maxCEMG(j,:),~]=svmEciton(savePath,'EMG',k,maxExpC,maxPerClass,eegOffset,true);
+         [meanAccurancysEEG(j),maxCEEG(j,:),~]=svmEciton(savePath,'EEG',k,maxExpC,maxPerClass,eegOffset,true);
+         [meanAccurancysLF(j),maxCLF(j,:),~]=svmEciton(savePath,'LF',k,maxExpC,maxPerClass,eegOffset,true);
 %         [meanAccurancysEMG(j),maxCEMG(j,:),cmScaledEMG(j,:,:)]=svmEciton(savePath,'EMG',k,maxExpC,maxPerClass,eegOffset,false);
 %         [meanAccurancysEEG(j),maxCEEG(j,:),cmScaledEEG(j,:,:)]=svmEciton(savePath,'EEG',k,maxExpC,maxPerClass,eegOffset,false);
 %         [meanAccurancysLF(j),maxCLF(j,:),cmScaledLF(j,:,:)]=svmEciton(savePath,'LF',k,maxExpC,maxPerClass,eegOffset,false);
@@ -107,12 +107,12 @@
 %         [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);
-        [correlationAutoencKin(j,:),maxRidgeParamIndexAutoencKin(j,:,:)]=ridgeCV(savePath,'Autoenc','kin',k,ridgeParams,eegOffset);
-        [correlationViaAutoenc(j,:),viaCorrelationAutoenc(j,:)]=ridgeCVvia(savePath,'EEG','Autoenc','kin',k,ridgeParams,eegOffset);
-        [correlationViaPCA(j,:),viaCorrelationPCA(j,:)]=ridgeCVvia(savePath,'EEG','PCA','kin',k,ridgeParams,eegOffset);
-        [correlationViaNNMF(j,:),viaCorrelationNNMF(j,:)]=ridgeCVvia(savePath,'EEG','NNMF','kin',k,ridgeParams,eegOffset);
-        [correlationEMGViaAutoenc(j,:),~]=ridgeCVvia(savePath,'EEG','Autoenc','EMG',k,ridgeParams,eegOffset);
+%        [correlationEEGemg(j,:),maxRidgeParamIndexEEGemg(j,:,:)]=ridgeCV(savePath,'EEG','EMG',k,ridgeParams,eegOffset);
+%        [correlationAutoencKin(j,:),maxRidgeParamIndexAutoencKin(j,:,:)]=ridgeCV(savePath,'Autoenc','kin',k,ridgeParams,eegOffset);
+%        [correlationViaAutoenc(j,:),viaCorrelationAutoenc(j,:)]=ridgeCVvia(savePath,'EEG','Autoenc','kin',k,ridgeParams,eegOffset);
+%        [correlationViaPCA(j,:),viaCorrelationPCA(j,:)]=ridgeCVvia(savePath,'EEG','PCA','kin',k,ridgeParams,eegOffset);
+%        [correlationViaNNMF(j,:),viaCorrelationNNMF(j,:)]=ridgeCVvia(savePath,'EEG','NNMF','kin',k,ridgeParams,eegOffset);
+%        [correlationEMGViaAutoenc(j,:),~]=ridgeCVvia(savePath,'EEG','Autoenc','EMG',k,ridgeParams,eegOffset);
         
         fprintf('%s%i finished %s\n',subject,number,datestr(datetime('now')))
     end
diff --git a/usedMcode/svmEciton.m b/usedMcode/svmEciton.m
index 7c688e4..7795a18 100644
--- a/usedMcode/svmEciton.m
+++ b/usedMcode/svmEciton.m
@@ -26,7 +26,7 @@
         classification=classification~=0;
     end
     
-    accurancy=zeros(k,3);
+    accuracy=zeros(k,3);
     maxC=zeros(k,1);
     noClasses=size(unique(classification),1);
     cm=zeros(noClasses);
@@ -41,10 +41,10 @@
         
         [model,maxC(i)]=kfoldCV(remainingClasses,remaining,k,maxExpC,maxPerClass);
 
-        [predictions,accurancy(i,:),~]=svmpredict(leaveClasses,leaveOut(:,:),model);
+        [predictions,accuracy(i,:),~]=svmpredict(leaveClasses,leaveOut(:,:),model);
         cm=cm+confusionmat(leaveClasses,predictions); %confusion matrix
     end
-    meanAccurancy=mean(accurancy(:,1));
+    meanAccurancy=mean(accuracy(:,1));
 
     cmScaled=zeros(size(cm));
     for i=1:size(cm,1)