diff --git a/text/thesis/04Discussion.tex b/text/thesis/04Discussion.tex
index 3f1bfa9..f2e5bdf 100644
--- a/text/thesis/04Discussion.tex
+++ b/text/thesis/04Discussion.tex
@@ -12,8 +12,7 @@
 \label{dis:eeg}
     Predictions from EEG to velocities and position are significantly better than those from EMG (see tables \ref{tab:pCorr},~\ref{tab:corrKin},~\ref{tab:pCorrPos} and \ref{tab:corrPos}).\\
     This might be because EMG has a hard time classifying the different movements due to massive activity while moving. This can be seen in the confusion matrix (\ref{fig:cmEMG}). Many data points belonging to class 2 or 4 are classified as 3 in error. The classification between movement and rest however works fine.\\
-    All in all few samples are classified as class 2 even though the training was done on a balanced set. This %TODO really?
-    could mean that features of class 2 are found in other classes too and by that do not have strong predictive power.
+    All in all few samples are classified as class 2 even though the training was done on a balanced set. This could mean that features of class 2 are found in other classes too and by that do not have strong predictive power.
 
     When predicting velocities or positions from EEG there is no significant difference between $x$ and $y$. The difference between $x$ and $y$ and the angle $\theta$ is larger for velocities than for absolute positions since the absolute angle prediction a lot better than the prediction of change.\\
     This again is an indication that the actual position is more important for the activity in brain than the change of position as itself.
@@ -24,7 +23,7 @@
     We show that the use of low frequencies (at least as we did it here) has no advantage over the use of EMG (see table \ref{tab:pCorr}). This might also be a hint that movement relics were have the biggest part in low frequencies while moving. This however makes it impossible to use them for continuous tasks.\\
     Low frequencies are great to early detect voluntary movement but are not applicable in our configuration.
 
-    Which is interesting nevertheless is, that low frequencies also occur in rest. Quite some of the movements are classified as rest (see figure \ref{fig:cmEEG}). If a sample is classified correctly as movement it is quite likely that is is also classified correctly - however with an preference on class 3 again. %TODO - naja
+    Which is interesting nevertheless is, that low frequencies also occur in rest. Quite some of the movements are classified as rest (see figure \ref{fig:cmFull}). If a sample is classified correctly as movement it is quite likely that is is also classified correctly - however with an preference on class 3 again. This matches the understanding of low frequencies as pre-movement activation mainly belonging to voluntary movement. The subjects probably plan all the possible movements while in rest to execute then once the stimulus was shown.
 \section{Velocities and Positions}
 \label{dis:velPos}
     We expected better performance when predicting velocities instead of absolute positions. Our findings however show the opposite. The performance is quite a lot better when predicting positions directly.\\