diff --git a/scripts/device_accuracy.py b/scripts/device_accuracy.py
index f330ac5..de78926 100644
--- a/scripts/device_accuracy.py
+++ b/scripts/device_accuracy.py
@@ -61,6 +61,13 @@ denovix_reference_values = {
             "1450": 0.447634285,
             "1550": 0.478220085,
         },
+        "HB": {
+            "2": 0.187191676,
+            "4": 0.187191676,
+            "5": 0.187191676,
+            "6": 0.187191676,
+            "8": 0.077846397,
+        },
     }
 df_reference_device = pd.DataFrame(denovix_reference_values).T
 df_reference_device.index.name = 'Solution'
@@ -70,14 +77,19 @@ df = pd.read_excel(curdir + path_delim + "data" + path_delim + "data_06_12_2023_
 
 if not df.empty:
     conditions = [df['name'].str.contains('Tar', case=False, na=False),
-                  df['name'].str.contains('KM', case=False, na=False)]
+                  df['name'].str.contains('KM', case=False, na=False),
+                  df['name'].str.contains('HB', case=False, na=False)]
     
-    choices = ['Tartrazine', 'KMnO4']
+    choices = ['Tartrazine', 'KMnO4', "HB"]
     
     df['solution'] = np.select(conditions, choices, default=None)
 
     def extract_numbers(s):
-        match = re.search(r'-(\d+)', s) or re.search(r'(\d+)', s)
+        if "HB" in s:
+            match = re.search(r'-(\d+)$', s)
+        else:
+            match = re.search(r'-(\d+)', s) or re.search(r'(\d+)', s)
+            
         if match:
             return int(match.group(1))
         else:
@@ -178,7 +190,7 @@ if not df.empty:
 
     fig, ax = plt.subplots()
 
-    filtered_df = df[df['solution'].isin(['KMnO4', 'Tartrazine'])]
+    filtered_df = df[df['solution'].isin(['KMnO4', 'Tartrazine', 'HB'])]
 
     for solution in filtered_df['solution'].unique():
         if pd.notna(solution):
@@ -199,8 +211,8 @@ if not df.empty:
             ax.text(concentration_means.index[-1] + 5, np.polyval(coefficients, concentration_means.index[-1]), annotation_text, fontsize=10, verticalalignment='center')
 
             wks1.write(row, 0, solution)
-            wks1.write(row, 1, coefficients[0])
-            wks1.write(row, 2, coefficients[1])
+            wks1.write(row, 1, str(coefficients[0]))
+            wks1.write(row, 2, str(coefficients[1]))
             
             row += 1
 
@@ -227,6 +239,5 @@ if not df.empty:
     writer.close()
 
 else:
-    # If df is empty, create an empty Excel file
     empty_output_filename = f'data/empty_excel_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx'
     pd.DataFrame().to_excel(empty_output_filename, engine='xlsxwriter', index=False)
\ No newline at end of file