diff --git a/text/TODO.txt b/text/TODO.txt
index 5ce9ceb..0fce01c 100644
--- a/text/TODO.txt
+++ b/text/TODO.txt
@@ -4,10 +4,14 @@
 
 pBurgOrder bestimmen
 
+filter -> filtfilt EMG
+
 Matching Bewegung EEG
   - Passt nicht zusammen - insgesamt ~40s zu wenig kin 
-  - durch ridge-Regression (EEG als feature)
-
+    + synchro Trigger (ch40)
+    + upsample_kin (in code)
+  - durch ridge-Regression (EMG dann EEG als feature)
+  - als Maß correlation
 
 
 ohne gridsearch vergleichen mit gridsearch
diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m
index 912372d..d0d6af9 100644
--- a/usedMcode/callAll.m
+++ b/usedMcode/callAll.m
@@ -2,11 +2,11 @@
 pathToFile='/nfs/wsi/ti/messor/hohlochj/origData/';
 % pathToFile='/home/jph/Uni/masterarbeit/Block1_ReachingMovements/';
 
-windowEMG=0.2;
+windowEMG=0.2; %try 1s
 windowEEG=1;
 shift=0.2;
 pburgOrder=50;
-minEEGFreq=0;
+minEEGFreq=0; %try 8-30
 maxEEGFreq=200;
 k=10;
 maxExpC=0;
@@ -37,5 +37,10 @@
         j=j+1;
     end
 end
-%save(sprintf('/nfs/wsi/ti/messor/hohlochj/matlabData/%s_callAll.mat',datestr(datetime('now'))));
+
+[ accEEG, accEMG, cmEEG, cmEMG ] = collectAccurancys( pathToFile, subjects, numbers );
+
+save(sprintf('/nfs/wsi/ti/messor/hohlochj/matlabData/%s_callAll.mat',datestr(datetime('now'))));
 delete(poolObj)
+
+
diff --git a/usedMcode/generateTrainingData.m b/usedMcode/generateTrainingData.m
index d188438..8462ce9 100644
--- a/usedMcode/generateTrainingData.m
+++ b/usedMcode/generateTrainingData.m
@@ -1,25 +1,34 @@
 function [trainingDataEEG,trainingDataEMG,kinPerSec] = generateTrainingData(signal,kin,windowEMG,windowEEG,shift,params,pburgOrder,minEEGFreq,maxEEGFreq)
-    frequency=params.SamplingRate.NumericValue;
-    signalWindowEMG=frequency*windowEMG;
-    signalWindowEEG=frequency*windowEEG;
+    bci_sf=params.SamplingRate.NumericValue;
+    signalWindowEMG=bci_sf*windowEMG;
+    signalWindowEEG=bci_sf*windowEEG;
     tempEEG=zeros([32,fix(floor(size(signal,1)/signalWindowEEG-1)*windowEEG/shift+1),maxEEGFreq-minEEGFreq+1]);
     tempEMG=zeros(fix([size(signal,2)-3-32,fix(size(signal,1)/signalWindowEMG-1)*windowEMG/shift+1]));
     
     %Filter around 50Hz and below 2 Hz
-    [A,B]= butter(2,[48 52]/(frequency/2),'stop');
-    [C,D]= butter(2,1/(frequency/2),'high');
-    [E,F]= butter(2,[148 152]/(frequency/2),'stop');
+    [A,B]= butter(2,[48 52]/(bci_sf/2),'stop');
+    [C,D]= butter(2,1/(bci_sf/2),'high');
+    [E,F]= butter(2,[148 152]/(bci_sf/2),'stop');
 
-    parfor i=1:32 %filter single channel, w/o HEOG, Synchro and 0s
-        tempEEG(i,:,:)=shiftingPburg(filtfilt(double(E),double(F),filtfilt(double(C),double(D),filtfilt(double(A),double(B),double(signal(:,i))))),frequency,windowEEG,shift,pburgOrder,minEEGFreq,maxEEGFreq);
+    parfor i=1:32 %filter single channel, w/o EMG, HEOG, Synchro and 0s
+        tempEEG(i,:,:)=shiftingPburg(filtfilt(double(E),double(F),filtfilt(double(C),double(D),filtfilt(double(A),double(B),double(signal(:,i))))),bci_sf,windowEEG,shift,pburgOrder,minEEGFreq,maxEEGFreq);
         %filtfilt stat filter
     end % TODO: 8-30Hz, pburg bei kurzen Fenstern (Ordnung: Je nach SamplingRate, bei 2500: 32-50, Alpha, Beta peaks sollten sichtbar sein)
     trainingDataEEG=permute(tempEEG,[2 1 3]);
     
     parfor i=33:size(signal,2)-3
-        tempEMG(i-32,:,:)=waveformLength(filter(C,D,filter(A,B,signal(:,i))),frequency,windowEMG,shift);
+        tempEMG(i-32,:,:)=waveformLength(filtfilt(double(E),double(F),filtfilt(double(C),double(D),filtfilt(double(A),double(B),double(signal(:,i))))),bci_sf,windowEMG,shift);
     end
     trainingDataEMG=permute(tempEMG,[2 1 3]);
     
+    %shift kin according to synch channel in first minute
+    [~,startingPoint]=max(abs(diff(signal(1:60*bci_sf,size(signal,2)-1))));
+    % add time offset in ms to kin-time
+    offset=startingPoint/bci_sf*1000;
+    kin(:,1)=kin(:,1)+offset;
+%     disp(offset)
+    %add dummy timestamp at the end to fill kinematics
+    kin=[kin;kin(end,:)];
+    kin(end,1)=size(trainingDataEEG,1)*1000*windowEEG;
     kinPerSec=shiftingKin(kin,windowEEG,shift);
 end
diff --git a/usedMcode/readEEG.m b/usedMcode/readEEG.m
index 1dab896..2c4b875 100644
--- a/usedMcode/readEEG.m
+++ b/usedMcode/readEEG.m
@@ -10,7 +10,7 @@
     for i=1:maxFile
         [sig, stat, params] = load_bcidat(strcat(pathToFile,sprintf('%s/%s_B100%i/%s_B1S00%iR0%i.dat',subject,subject,number,subject,number,i)));
         tmpKin=csvread(strcat(pathToFile,sprintf('kin/%s_B1S00%iR0%i.txt',subject,number,i)),1,0);
-        [trainingDataEEGcell{i},trainingDataEMGcell{i},kin{i}]=generateTrainingData(sig,tmpKin,windowEMG,windowEEG,shift,params,pburgOrder,minEEGFreq,maxEEGFreq);
+        [trainingDataEEGcell{i},trainingDataEMGcell{i},kin{i}]=generateTrainingData(sig,tmpKin(1:4),windowEMG,windowEEG,shift,params,pburgOrder,minEEGFreq,maxEEGFreq);
         classesCell{i}=stat.StimulusCode;
         %fprintf('%ith file processed\n',i)
     end
diff --git a/usedMcode/shiftingKin.m b/usedMcode/shiftingKin.m
index 2a62296..a7a7cd4 100644
--- a/usedMcode/shiftingKin.m
+++ b/usedMcode/shiftingKin.m
@@ -1,6 +1,6 @@
 function [kinPerSec]=shiftingKin(kin, window, shift)
-    kinPerSec=zeros(fix((max(kin(:,1))-window*1000)/(shift*1000)),3);
+    kinPerSec=zeros(fix((max(kin(:,1))-window*1000)/(shift*1000)),4);
     for j=1:fix((max(kin(:,1))-window*1000)/(shift*1000))
-        kinPerSec(j,:)=sum(diff(kin(kin(:,1)>(j-1)*shift*1000 & kin(:,1)<=(j-1)*shift*1000+window*1000,2:4)));
+        kinPerSec(j,:)=sum(diff(kin(kin(:,1)>(j-1)*shift*1000 & kin(:,1)<=(j-1)*shift*1000+window*1000,:)));
     end
 end
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