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README.md

@@ -13,31 +13,37 @@ pinned: false
 
 This project is a Deep Learning-based arrhythmia detection system that classifies signals into:
 
-- Bradycardia
-- Tachycardia
-- Ventricular Fibrillation (VFib)
-- Ventricular Tachycardia (VTach)
-- Normal
-
-### 🔍 Input
-Upload `.csv` files containing:
-- Time
-- ECG (II/III/AVF/I)
-- PPG/Pleth
-
-### ⚙️ Model
-- Architecture: CNN + LSTM
-- Input: Raw segmented ECG and PPG signals (20s window, 10s overlap)
-- Framework: TensorFlow/Keras
-
-### 🧠 Output
-- Predicted Class
-- Confidence Score
-- Segment-wise classification
-- Optional signal visualization (first 10 seconds)
+- **Bradycardia**
+- **Tachycardia**
+- **Ventricular Fibrillation (VFib)**
+- **Ventricular Tachycardia (VTach)**
+- **Normal**
 
 ---
 
-### 🚀 Created by
-Mathivani | Final Year B.Tech Biomedical Engineering  
+## 🔍 Input  
+Upload `.csv` files containing:  
+- Time  
+- ECG (II/III/AVF/I)  
+- PPG/Pleth  
+
+---
+
+## ⚙️ Model  
+- Architecture: CNN + LSTM  
+- Input: Raw segmented ECG and PPG signals (20s window, 10s overlap)  
+- Framework: TensorFlow/Keras  
+
+---
+
+## 🧠 Output  
+- Predicted Class  
+- Confidence Score  
+- Segment-wise classification  
+- Optional signal visualization (first 10 seconds)  
+
+---
+
+## 🚀 Created by  
+**Mathivani** | Final Year B.Tech Biomedical Engineering  
 SRM Institute of Science and Technology