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pip install -r requirements.txt1import numpy as np
2from tensorflow import keras
3
4# Load pre-trained model
5model = keras.models.load_model('path/to/your/model.h5')
6
7# Your EEG data (1 second, 64 channels, 250 Hz sampling)
8eeg_data = np.random.randn(250, 64) # Replace with real EEG
9
10# Make prediction
11prediction = model.predict(eeg_data.reshape(1, 250, 64))
12classes = ['Up', 'Down', 'Left', 'Right']
13predicted_command = classes[np.argmax(prediction)]
14
15print(f"Predicted command: {predicted_command}")
16print(f"Confidence: {np.max(prediction):.3f}")1from analysis import InnerSpeechAnalyzer
2
3# Initialize predictor
4analyzer = InnerSpeechAnalyzer('path/to/your/model.h5')
5predictor = analyzer.create_real_time_predictor()
6
7# Real-time loop
8while True:
9 eeg_data = capture_eeg_signal() # Your EEG acquisition function
10 command, confidence = predictor.predict_thought(eeg_data)
11
12 if confidence > 0.8:
13 execute_command(command) # Your command execution
14 print(f"Executing: {command}")1tensorflow>=2.8.0,<3.0.0
2scikit-learn>=1.0.0
3numpy>=1.21.0
4scipy>=1.7.0
5pandas>=1.3.0
6mne>=1.0.0
7matplotlib>=3.5.0
8seaborn>=0.11.01# User thinks "forward" → wheelchair moves forward
2# User thinks "left" → wheelchair turns left1# User thinks "up" → lights turn on
2# User thinks "down" → lights turn off1# User thinks "right" → character moves right
2# Mental commands for game control