학술논문

Mapping Information Flow of Independent Source to Predict Conscious Level: A Granger Causality Based Brain-Computer Interface
Document Type
Conference
Source
2012 International Symposium on Computer, Consumer and Control Computer, Consumer and Control (IS3C), 2012 International Symposium on. :813-816 Jun, 2012
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Brain modeling
Electroencephalography
Humans
Data models
Support vector machines
Neuroscience
Brain computer interfaces
Granger causality
support vector regression
brain-computer interface
traffic safty
Language
Abstract
Recent studies have shown that the various brain networks over different cognitive states. In contrast to measure a physiological change over a single region, the information flows between brain regions described by effective connectivity provides an informative dynamic over the whole brain. In this study, we proposed a source information flow network based on the combination of Granger causality and support vector regression to predict driver's conscious level. This work provides the first application of using brain network to develop a brain-computer interface and obtain a sound result of performance.