Mozartuss/DEAP-Emotion-Recognition

Emotion Recogniton LSTM RNN Arousal Valence

40
/ 100
Emerging

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.

No commits in the last 6 months.

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.

neuroscience EEG analysis emotion detection psychophysiology human-computer interaction
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

63

Forks

11

Language

Python

License

Apache-2.0

Last pushed

Mar 02, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Mozartuss/DEAP-Emotion-Recognition"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.