diff --git a/README.md b/README.md
index 7c9154e..4a76aa7 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,7 @@
 An interactive Python Dash app to visualize, analyze, and explore your jogging or running sessions recorded as GPX/FIT files.
 
 <p align="left">
-    <img src="WebAppGPXDashboard.jpg" alt="Description" width="800">
+    <img src="WebAppFITDashboard.png" alt="Description" width="800">
 </p>
 
 ---
diff --git a/WebAppFITDashboard.png b/WebAppFITDashboard.png
new file mode 100644
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diff --git a/WebAppGPXDashboard.jpg b/WebAppGPXDashboard.jpg
deleted file mode 100644
index 891295c..0000000
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diff --git a/WebAppGPXDashboard.png b/WebAppGPXDashboard.png
new file mode 100644
index 0000000..b7ad910
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diff --git a/fit_app.py b/fit_app.py
index d5526b3..23c8c9e 100644
--- a/fit_app.py
+++ b/fit_app.py
@@ -27,13 +27,10 @@ from fitparse import FitFile
 
 # === Helper Functions ===
 def list_fit_files():
-    folder = './fit_files'  # Ordnerpfad anpassen
-    if not os.path.exists(folder):
-        os.makedirs(folder)
-
+    folder = './fit_files'
     files = [f for f in os.listdir(folder) if f.lower().endswith('.fit')]
 
-    # Datum extrahieren für Sortierung
+    # Extract date from the start of the filename and sort descending
     def extract_date(filename):
         try:
             return datetime.datetime.strptime(filename[:10], '%d.%m.%Y')  # Format DD.MM.YYYY
@@ -523,6 +520,7 @@ def create_heart_rate_plot(df):
         mode='lines',
         #name='Geglättete Herzfrequenz',
         line=dict(color='#E43D70', width=2),
+        showlegend=False,
         hovertemplate=(
             "Zeit: %{x}<br>" +
             "Herzfrequenz: %{y:.0f} bpm<br>" +
@@ -530,18 +528,18 @@ def create_heart_rate_plot(df):
         )
     ))
 
-    # Optional: Raw Heart Rate als dünnere, transparente Linie
-    if not df['heart_rate'].isna().all():
-        fig.add_trace(go.Scatter(
-            x=df['time'],
-            y=df['heart_rate'],
-            mode='lines',
-            name='Raw Herzfrequenz',
-            line=dict(color='#E43D70', width=1, dash='dot'),
-            opacity=0.3,
-            showlegend=False,
-            hoverinfo='skip'
-        ))
+    # # Optional: Raw Heart Rate als dünnere, transparente Linie
+    # if not df['heart_rate'].isna().all():
+    #     fig.add_trace(go.Scatter(
+    #         x=df['time'],
+    #         y=df['heart_rate'],
+    #         mode='lines',
+    #         name='Raw Herzfrequenz',
+    #         line=dict(color='#E43D70', width=1, dash='dot'),
+    #         opacity=0.3,
+    #         showlegend=False,
+    #         hoverinfo='skip'
+    #     ))
 
     # Durchschnittslinie
     if mean_hr > 0:
@@ -569,31 +567,30 @@ def create_heart_rate_plot(df):
 
     # Heart Rate Zonen (optional)
     if mean_hr > 0:
-        # Geschätzte maximale Herzfrequenz (220 - Alter, hier als Beispiel 190)
-        max_hr_estimated = 190  # Du kannst das anpassen
+        # Geschätzte maximale Herzfrequenz (Beispiel: 200 bpm)
+        # Heart Rate Zonen (optional)
+        # Geschätzte maximale Herzfrequenz
+        max_hr_estimated = 200  # oder z. B. 220 - alter
 
-        # Zone 1: Sehr leicht (50-60% HRmax)
-        zone1_lower = max_hr_estimated * 0.5
-        zone1_upper = max_hr_estimated * 0.6
+        # Definiere feste HR-Zonen in BPM
+        zones = [
+            {"name": "Zone 1", "lower": 0,   "upper": 124, "color": "#F4A4A3"},
+            {"name": "Zone 2", "lower": 124, "upper": 154, "color": "#EF7476"},
+            {"name": "Zone 3", "lower": 154, "upper": 169, "color": "#EA4748"},
+            {"name": "Zone 4", "lower": 169, "upper": 184, "color": "#E02628"},
+            {"name": "Zone 5", "lower": 184, "upper": max_hr_estimated, "color": "#B71316"},
+        ]
 
-        # Zone 2: Leicht (60-70% HRmax)
-        zone2_upper = max_hr_estimated * 0.7
-
-        # Zone 3: Moderat (70-80% HRmax)
-        zone3_upper = max_hr_estimated * 0.8
-
-        # Zone 4: Hart (80-90% HRmax) #update: bis 100%
-        zone4_upper = max_hr_estimated * 1.0
-
-        # Füge Zonen-Bereiche als Hintergrundbereiche hinzu
-        fig.add_hrect(y0=zone1_lower, y1=zone1_upper,
-                     fillcolor="green", opacity=0.1, line_width=0)
-        fig.add_hrect(y0=zone1_upper, y1=zone2_upper,
-                     fillcolor="yellow", opacity=0.1, line_width=0)
-        fig.add_hrect(y0=zone2_upper, y1=zone3_upper,
-                     fillcolor="orange", opacity=0.1, line_width=0)
-        fig.add_hrect(y0=zone3_upper, y1=zone4_upper,
-                     fillcolor="red", opacity=0.1, line_width=0)
+        # Zeichne Zonen als Hintergrund (horizontale Rechtecke)
+        for zone in zones:
+            fig.add_hrect(
+                y0=zone["lower"], y1=zone["upper"],
+                fillcolor=zone["color"],
+                opacity=0.1,
+                line_width=0,
+                annotation_text=zone["name"],  # optional: Name der Zone einblenden
+                annotation_position="top left"
+            )
 
     # Layout
     title_text = f'Herzfrequenz über die Zeit (geglättete)'