A BCI using VEP for continuous control of a mobile robot
| Autor: | R. Pruckl, Angelika Peer, Mohammad Abu-Alqumsan, Christoph Kapeller, Christoph Guger, Christoph Hintermüller |
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| Rok vydání: | 2013 |
| Předmět: |
Adult
Computer science Speech recognition Interface (computing) 0206 medical engineering 02 engineering and technology Electroencephalography Signal-To-Noise Ratio Feedback 03 medical and health sciences 0302 clinical medicine Software medicine Humans Computer vision Brain–computer interface medicine.diagnostic_test business.industry Mobile robot Equipment Design Robotics 020601 biomedical engineering Nontherapeutic Human Experimentation Brain-Computer Interfaces Robot Evoked Potentials Visual Artificial intelligence business 030217 neurology & neurosurgery Photic Stimulation |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | A brain-computer interface (BCI) translates brain activity into commands to control devices or software. Common approaches are based on visual evoked potentials (VEP), extracted from the electroencephalogram (EEG) during visual stimulation. High information transfer rates (ITR) can be achieved using (i) steady-state VEP (SSVEP) or (ii) code-modulated VEP (c-VEP). This study investigates how applicable such systems are for continuous control of robotic devices and which method performs best. Eleven healthy subjects steered a robot along a track using four BCI controls on a computer screen in combination with feedback video of the movement. The average time to complete the tasks was (i) 573.43 s and (ii) 222.57 s. In a second non-continuous trial-based validation run the maximum achievable online classification accuracy over all subjects was (i) 91.36 % and (ii) 98.18 %. This results show that the c-VEP fits the needs of a continuous system better than the SSVEP implementation. |
| Databáze: | OpenAIRE |
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