diff --git a/Matlab/eeg_load_xdf.m b/Matlab/eeg_load_xdf.m
index f344bd5..ac14ed3 100644
--- a/Matlab/eeg_load_xdf.m
+++ b/Matlab/eeg_load_xdf.m
@@ -13,7 +13,10 @@
 %                                (default: 'EEG')
 %
 %                'effective_rate' : if true, use the effective sampling rate instead of the nominal
-%                                   sampling rate (as declared by the device) (default: false)
+%                                   sampling rate (as declared by the device). Note that using
+%                                   effective_rate can lead to incorrect results if the nominal
+%                                   sampling rate is 0 (i.e. non constant sample interval)
+%                                   (default: false)
 %
 %                'exclude_markerstreams' : can be a cell array of stream names to exclude from
 %                                          use as marker streams (default: {})
diff --git a/Matlab/xdf/load_xdf.m b/Matlab/xdf/load_xdf.m
index 0792c17..4409d6d 100644
--- a/Matlab/xdf/load_xdf.m
+++ b/Matlab/xdf/load_xdf.m
@@ -348,6 +348,7 @@
             if temp(id).srate > 0
                 temp(id).sampling_interval = 1/temp(id).srate;
             else
+                warning('Nominal sampling rate of stream %s is 0. Calculated effective sampling rate might not be meaningful, relying on this rate is not recommended.', header.info.name);
                 temp(id).sampling_interval = 0;
             end
             % fread parsing format for data values
@@ -552,10 +553,10 @@
                 end
 
                 % calculate the weighted mean sampling rate over all segments
-                temp(k).effective_rate = sum(bsxfun(@times,[segments.effective_srate],[segments.num_samples]/sum([segments.num_samples])));            
+                temp(k).effective_srate = sum(bsxfun(@times,[segments.effective_srate],[segments.num_samples]/sum([segments.num_samples])));
 
                 % transfer the information into the output structs
-                streams{k}.info.effective_srate = temp(k).effective_rate;
+                streams{k}.info.effective_srate = temp(k).effective_srate;
                 streams{k}.segments = segments;
             end
         end
@@ -563,7 +564,14 @@
 else
     % calculate effective sampling rate
     for k=1:length(temp)
-        temp(k).effective_srate = (length(temp(k).time_stamps) - 1) / (temp(k).time_stamps(end) - temp(k).time_stamps(1)); end
+        if length(temp(k).time_stamps) > 0
+            temp(k).effective_srate = (length(temp(k).time_stamps) - 1) / (temp(k).time_stamps(end) - temp(k).time_stamps(1));
+        else
+            temp(k).effective_srate = 0;
+        end
+        % transfer the information into the output structs
+        streams{k}.info.effective_srate = temp(k).effective_srate;
+    end
 end
 
 % copy the information into the output