EEG-Based Cognitive Interfaces for Ubiquitous Applications: Developments and Challenges
IEEE Intelligent Systems2011Vol. 26(5), pp. 46–53
Citations Over TimeTop 10% of 2011 papers
Bin Hu, Dennis Majoe, Martyn Ratcliffe, Yanbing Qi, Qinglin Zhao, Hong Peng, Dangping Fan, Fang Zheng, Mike Jackson, Philip Moore
Abstract
Technical advances in the neuroelectric recordings and in the computational tools for the analysis of the brain activity and connectivity make it now possible to follow and to quantify, in real time, the interactive brain activity in a group of subjects engaged in social interactions. The degree of interaction between persons can then be assessed by "reading" their neuroelectric activities. Imaging the social brain can thus open a new area of study in neuroscience.
Related Papers
- → Comparing the quality of signals recorded with a rapid response EEG and conventional clinical EEG systems(2019)46 cited
- → Which electroencephalography (EEG) for epilepsy? The relative usefulness of different EEG protocols in patients with possible epilepsy(2006)100 cited
- → Time Series of Awake Background EEG Generated by a Model Reflecting the EEG Report(2007)
- → Sleep stage detection using chaotic feature analysis of Electroencephalography (EEG) signals(2022)
- → Comparison of awake Electroencephalography, Electroencephalography after Sleep Deprivation, and Melatonin-Induced Sleep Electroencephalography Sensitivity in the Diagnosis of Epilepsy in Adults(2022)