diff --git a/usedMcode/balanceClasses.m b/usedMcode/balanceClasses.m
index 54e7ba0..59bdcd6 100644
--- a/usedMcode/balanceClasses.m
+++ b/usedMcode/balanceClasses.m
@@ -1,11 +1,12 @@
 function [trainClasses,trainData]=balanceClasses(trainClasses,trainData,maxPerClass,noClasses)
-%     if maxPerClass > min(histcounts(trainClasses,noClasses))
-%         maxPerClass=min(histcounts(trainClasses));
-%         warning('not enough Data per Class; set maxPerClass to %i', maxPerClass);
-%     end
+    if maxPerClass > min(histcounts(trainClasses,noClasses))
+        maxPerClass=min(histcounts(trainClasses));
+        warning('not enough Data per Class; set maxPerClass to %i', maxPerClass);
+    end
     i=1;
+    % number of elements per class that has to be deleted
     delPerClass=histcounts(trainClasses,noClasses)-maxPerClass;
-    delIndex=zeros(sum(delPerClass),1);
+    delIndex=zeros(sum(delPerClass),1); % collects the indices that will be deleted
     while sum(delPerClass)>0
         r=fix(size(trainClasses,1)*rand(1)+1);
         if delPerClass(trainClasses(r)+1)>0 && all(delIndex~=r)
diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m
index ba53275..b31acb6 100644
--- a/usedMcode/callAll.m
+++ b/usedMcode/callAll.m
@@ -8,22 +8,27 @@
 
 allSubjects=true; %run all subjects and days or only one random day for one random subject
 name='MoveRest'; %suffix for the output, has to be valid name for file (no space, /, ...)
-windowEMG=0.2;
+
+% window and shift given in seconds
+windowEMG=0.2; 
 windowEEG=1;
 shiftEMG=0.05;
 shiftEEG=0.2;
 eegOffset=0; %predict actions x*shiftEEG after EEG measurement
 pburgOrder=250;
-minEEGFreq=2;
+minEEGFreq=2; %[Hz]
 maxEEGFreq=49;
-pause=false;
+pause=false; % is all data 1s befor movement dropped?
 noLFsamples=5;
+% Parameters tried for ridge regression
 ridgeParams=100;
-k=10;
+k=10; % k-fold CV (usually 10)
+% Parameters tried for SVM: 2^-x to 2^x in steps of 1 in x
 maxExpC=0;
 maxPerClass=250;
 poolObj=parpool(32);
 
+% structer data of runs
 [subjects,numbers]=namesAndNumbers(pathToFile);
 numbersMat=cell2mat(numbers);
 subjectsForNumbers=cell(size(numbersMat,2),1);
@@ -37,7 +42,7 @@
 end
 j=j-1; %number of trial-days for all subjects
 
-
+% run for all 51 runs
 if allSubjects
     
      meanAccuracysEMG=zeros([j,1]);
@@ -125,6 +130,7 @@
     
     save(strcat(pathToFile,sprintf('../matlabData/%s_callAll-%s.mat',datestr(datetime('now')),name)));
 else
+    % runn only for one random run
     j=fix(rand()*size(numbersMat,2)+1);
     
     number=numbersMat(j);