diff --git a/src/features/phone_esm/straw/process_user_event_related_segments.py b/src/features/phone_esm/straw/process_user_event_related_segments.py
index 3f75359e..3762d59a 100644
--- a/src/features/phone_esm/straw/process_user_event_related_segments.py
+++ b/src/features/phone_esm/straw/process_user_event_related_segments.py
@@ -39,7 +39,6 @@ def extract_ers_from_file(esm_df, device_id):
     esm_df = esm_preprocessed.loc[(esm_preprocessed['device_id'].isin(esm_filtered_sessions['device_id'])) & (esm_preprocessed['esm_session'].isin(esm_filtered_sessions['esm_session']))]
     
 
-
     # Problem ne bo ekstrahiranje posameznih začetkov in trajanj stresnih dogodkov - večji problem je pridobitev ustreznega targeta, 
     # tako da bo poravnan s tem dogodkom, saj se lahko zgodi, da je timestamp zabeležene intenzitete stresnega dogodka ne pade v okno stresnega dogodka.
     # Edina izjema tega so, če je označen odgovor "1 - Še vedno traja" pri vprašanju appraisal_event_duration
@@ -70,10 +69,12 @@ def extract_ers_from_file(esm_df, device_id):
 
             extracted_ers['diffs'] = extracted_ers['event_timestamp'].astype('int64') - extracted_ers['end_event_timestamp'].shift(1, fill_value=0).astype('int64')
             extracted_ers.loc[extracted_ers['diffs'] > time_before_questionnaire * 1000, 'diffs'] = time_before_questionnaire * 1000
+            
+            extracted_ers["diffs"] = (extracted_ers["diffs"] / 1000).apply(lambda x: math.ceil(x))
 
-            # TODO: združi celotno trajanje in formatiraj v HH:MM:SS
+            extracted_ers["length"] = (extracted_ers["timestamp"] + extracted_ers["diffs"]).apply(lambda x: format_timestamp(x))
+            extracted_ers["shift"] = extracted_ers["diffs"].apply(lambda x: format_timestamp(x))
 
-            sys.exit()
     elif targets_method == "stress_events":
         pass
         # VV Testiranje različnih povpraševanj za VV
@@ -83,9 +84,9 @@ def extract_ers_from_file(esm_df, device_id):
         # print(filter_esm.shape)
         
     else:
+        raise Exception("Please select correct target method for the event-related segments.")
         extracted_ers = pd.DataFrame(columns=["label", "event_timestamp", "length", "shift", "shift_direction", "device_id"])
 
-    sys.exit()
     return extracted_ers[["label", "event_timestamp", "length", "shift", "shift_direction", "device_id"]]
 
 if snakemake.params["stage"] == "extract":