Self-Paced (Asynchronous) BCI Control of a Wheelchair in Virtual Environments: A Case Study with a Tetraplegic

By Robert Leeb, D. Friedman, Gernot R. Müller-Putz, Reinhold Scherer, Mel Slater, Gert Pfurtscheller. Computational Intelligence and Neuroscience, 2007

521 citations recorded by the source corpus.

The aim of the present study was to demonstrate for the first time that brain waves can be used by a tetraplegic to control movements of his wheelchair in virtual reality (VR). In this case study, the spinal cord injured (SCI) subject was able to generate bursts of beta oscillations in the electroencephalogram (EEG) by imagination of movements of his paralyzed feet. These beta oscillations were used for a self-paced (asynchronous) brain-computer interface (BCI) control based on a single bipolar EEG recording. The subject was placed inside a virtual street populated with avatars. The task was to “go” from avatar to avatar towards the end of the street, but to stop at each avatar and talk to them. In average, the participant was able to successfully perform this asynchronous experiment with a performance of 90%, single runs up to 100%.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/c39c8f83b121693131985b4eda2035e85e40f6ae

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

1. Bin He
2. Bryan S. Baxter
3. Yili Liu
4. Luzheng Bi
5. Bradley Jay Edelman
6. Xinan Fan

In Cognitive Neuroscience

1. Bryan S. Baxter
2. Bradley Jay Edelman
3. Bin He
4. Yili Liu
5. Luzheng Bi
6. Xinan Fan
7. Jonathan R. Wolpaw
8. Dennis J. McFarland

In Human-Computer Interaction

1. Bin He
2. Yili Liu
3. Luzheng Bi
4. Xinan Fan

Citations in the corpus

• EEG-Based Brain-Controlled Mobile Robots: A Survey (2013, methodology): “only go forward and stop [25]; 2) a subject suffering from ALS was applied to evaluate the proposed BCI telepresence robotic system [51]; and 3) Millán et al.”
• Brain-Computer Interfaces for Communication and Control (2011, unknown): “10,14 Bell et al. 1 showed the P300 could be used to select among complex commands to a partially autonomous humanoid robot; for a review of the use of BCI for robotic and prosthetic devices see McFarland and Wolpaw.”
• EEG Source Imaging Enhances the Decoding of Complex Right Hand Motor Imagery Tasks (2015, background): “SMR BCIs in particular have been incorporated into many real-life situations by controlling devices such as wheelchairs [45], limb”