Journal of Neural Engineering · 2008 · 389 citations · 21 references
EngineeringComputer ScienceNeuroscienceHumanoid RoboticsRobot ControlRoboticsBrain-computer InterfacesElectroencephalographyHuman-machine InterfacesRobot NavigationBrain-computer Interface Signal ProcessingBrain-machine InterfacesElectroencephalography-based Brain-computer InterfacesHuman-robot NavigationHumanoid WalkingNoninvasive Brain-computer InterfacesSignal-to-noise RatioVisual Feedback
EEG has been used for cursor control and spelling, but its low signal‑to‑noise ratio has made it unlikely for complex control. The study presents an EEG‑based brain‑computer interface that enables users to command a partially autonomous humanoid robot to perform complex tasks such as walking to specific locations and picking up objects. The system uses noninvasive scalp EEG signals and visual feedback from the robot’s cameras to allow users to select arbitrary objects for pick‑up and transport. In a study of nine users, the interface achieved 95 % accuracy in selecting one of four commands within 5 s, demonstrating that EEG can support sophisticated robotic navigation, manipulation, and transport.
We describe a brain–computer interface for controlling a humanoid robot directly using brain signals obtained non-invasively from the scalp through electroencephalography (EEG). EEG has previously been used for tasks such as controlling a cursor and spelling a word, but it has been regarded as an unlikely candidate for more complex forms of control owing to its low signal-to-noise ratio. Here we show that by leveraging advances in robotics, an interface based on EEG can be used to command a partially autonomous humanoid robot to perform complex tasks such as walking to specific locations and picking up desired objects. Visual feedback from the robot's cameras allows the user to select arbitrary objects in the environment for pick-up and transport to chosen locations. Results from a study involving nine users indicate that a command for the robot can be selected from four possible choices in 5 s with 95% accuracy. Our results demonstrate that an EEG-based brain–computer interface can be used for sophisticated robotic interaction with the environment, involving not only navigation as in previous applications but also manipulation and transport of objects.
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Chih-Chung Chang, Chih‐Jen Lin · ACM Transactions on Intelligent Systems and Technology · 2011 · 41.3K citations
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Leigh R. Hochberg, Mijail D. Serruya, Gerhard M. Friehs et al. · Nature · 2006 · 3.3K citations