nasoboleva/EEG-Emotion-Recognition
EEG data processing and it's convolution using AutoEncoder + CNN + RNN
This project helps neuroscientists and medical researchers analyze raw EEG brainwave data to automatically detect and classify emotional states. It takes complex, high-dimensional EEG signals as input and outputs classifications of specific emotions. It's designed for professionals studying brain activity and emotional responses.
No commits in the last 6 months.
Use this if you need to process raw EEG data and automatically identify emotional states, potentially for early detection of neurological conditions.
Not ideal if your primary goal is general brain behavior analysis beyond emotion recognition or if you don't work with EEG data.
Stars
96
Forks
22
Language
Jupyter Notebook
License
—
Category
Last pushed
May 23, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/nasoboleva/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...