Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems.
Journal:
Journal of neural engineering
Published Date:
Jun 1, 2017
Abstract
OBJECTIVE: This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations.
Authors
Keywords
Adaptation, Physiological
Algorithms
Biofeedback, Psychology
Brain-Computer Interfaces
Computer Simulation
Goals
Humans
Man-Machine Systems
Models, Statistical
Pattern Recognition, Automated
Psychomotor Performance
Reproducibility of Results
Robotics
Sensitivity and Specificity
User-Computer Interface