Mozartuss/DEAP-Emotion-Recognition
Emotion Recogniton LSTM RNN Arousal Valence
This project helps researchers and scientists analyze raw electroencephalogram (EEG) data to understand human emotional states. It takes raw EEG recordings (brainwave signals) as input and outputs classifications of emotional arousal and valence (how pleasant or unpleasant an emotion is). This is primarily for neuroscientists, psychologists, and human-computer interaction researchers interested in objective emotion detection.
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Use this if you are a researcher working with EEG data and need to accurately classify emotional states (arousal and valence) from brainwave signals.
Not ideal if you are looking for a plug-and-play solution for real-time emotion detection in a clinical or commercial setting without prior research expertise.
Stars
63
Forks
11
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 02, 2023
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