diff --git a/main.py b/main.py
index 87517a8f387d3b81d4e5630c00226c353b21323a..f9655e43f19d4fd32044bf47bf9164f31f851a34 100644
--- a/main.py
+++ b/main.py
@@ -1,6 +1,7 @@
 import scipy.io
+import numpy as np
 from scipy.signal import butter, filtfilt
-import scipy.signal
+import matplotlib.pyplot as plt
 
 def load_emg_data(file_path):
 
@@ -25,8 +26,8 @@ def load_emg_data(file_path):
     return channel_names
 
 
-file_path = "emg_data_walking.mat"
-load_emg_data(file_path)
+#file_path = "emg_data_walking.mat"
+#load_emg_data(file_path)
 
 chosen_muscles = {
     'rectus_fomoris': 0,
@@ -43,7 +44,7 @@ class DataRetrieval:
     def load_data(self):
         mat_data = scipy.io.loadmat(self.file_path)
         self.emg_data = mat_data['emg_data_walking']
-        self.channel_names = emg_data['data_headers'][0][0]
+        self.channel_names = self.emg_data['data_headers'][0][0]
         self.channel_names = [ch[0] for ch in self.channel_names[0]]
 
     def get_channel_names(self):
@@ -63,15 +64,50 @@ class SignalProcessing:
         pass
 
 #print(dir(scipy.signal))
-mat_data = scipy.io.loadmat('emg_data_walking.mat')
-emg_data = mat_data['emg_data_walking']
 
-sampling_rate = emg_data['sampling_rate'][0][0][0]
 
-data = emg_data['data'][0][0]
-num_samples = data.shape[1]
+def info_emg_data(file_path):
+    mat_data = scipy.io.loadmat(file_path)
+    emg_data = mat_data['emg_data_walking']
+
+    sampling_rate = emg_data['sampling_rate'][0][0][0]
+
+    data = emg_data['data'][0][0]
+    num_samples = data.shape[1]
+
+    duration = num_samples / sampling_rate
+    return sampling_rate, data, num_samples, duration
+
+#file_path = "emg_data_walking.mat"
+#info_emg_data(file_path)
+
+def plot_emg_data(file_path):
+    sampling_rate, data, num_samples, duration = info_emg_data(file_path)
+
+    sampling_time = float(1/sampling_rate)
+    time_vector = np.arange(0,duration,sampling_time)
+    channel_rectus_femoris = data[chosen_muscles['rectus_fomoris'], :]
+    channel_tibialis_anterior = data[chosen_muscles['tibialis_anterior'], :]
+
+    plt.figure(figsize=(10,6))
+
+    plt.subplot(2, 1, 1)
+    plt.plot(time_vector, channel_rectus_femoris)
+    plt.title('EMG Data - Rectus femoris')
+    plt.xlabel('Time [Seconds]')
+    plt.ylabel('Amplitude')
+
+    plt.subplot(2, 1, 2)
+    plt.plot(time_vector, channel_tibialis_anterior)
+    plt.title('EMG Data - Tibialis Anterior')
+    plt.xlabel('Time [seconds]')
+    plt.ylabel('Amplitude')
+
+    plt.tight_layout()
+    plt.show()
+
+file_path = "emg_data_walking"
+plot_emg_data(file_path)
+
+
 
-duration = num_samples / sampling_rate
-print(f"Sampling frequentie: {sampling_rate} Hz")
-print(f"Aantal samples: {num_samples}")
-print(f"Lengte van de data: {duration}")