OpenAlex
metadata only
CC BY 4.0
Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
artificial-intelligencebrain-computer-interfacecomputer-scienceconvolutional-neural-networkelectroencephalographysupport-vector-machine
Abstract Affective computing, a subcategory of artificial intelligence, detects, processes, interprets, and mimics human emotions. Thanks to the continued advancement of portable non-invasive human sensor technologies, like brain–computer interfaces (BCI), emotion recognition has piqued the interest
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies \n on Signal Sensing Technologies and Computational Intelligence Approaches and \n their Applications#477093
- A 2-Block Architecture for Real-Time EEG Gait Decoding: A Pilot Study#610017
- A 2-Block Architecture for Real-Time EEG Gait Decoding: A Pilot Study#608955
- Investigation of Oscillations Underlying Human Cognitive and Affective Processing Using Intracranial EEG#898131
- Non-Invasive Brain-Computer Interface for Virtual Object Control#897082
Record · ID 976543
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive