shyammarjit/EEG-Emotion-Recognition
EEG-Based Emotion Recognition
This project helps researchers and practitioners in affective computing and human-computer interaction to automatically identify human emotional states. It takes raw EEG (Electroencephalography) brainwave data and classifies it into different emotional categories, such as high/low valence and arousal. The output is a prediction of the emotional state, helping users understand and interpret physiological responses to stimuli.
No commits in the last 6 months.
Use this if you need to classify emotional states from EEG data with high accuracy for research or application development.
Not ideal if you are looking for real-time, low-latency emotion recognition on embedded devices or with non-EEG biometric data.
Stars
69
Forks
12
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 09, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/shyammarjit/EEG-Emotion-Recognition"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
mne-tools/mne-python
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
braindecode/braindecode
Deep learning software to decode EEG, ECG or MEG signals
NeuroTechX/moabb
Mother of All BCI Benchmarks
neuromodulation/py_neuromodulation
Real-time analysis of intracranial neurophysiology recordings.
IoBT-VISTEC/MIN2Net
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE...