title: Answering questions with an electroencephalogram-based brain-computer interface.
abstract: OBJECTIVE
  To demonstrate that humans can learn to control selected electroencephalographic components and use that control to answer simple questions.
  
  
  METHODS
  Four adults (one with amyotrophic lateral sclerosis) learned to use electroencephalogram (EEG) mu rhythm (8 to 12Hz) or beta rhythm (18 to 25Hz) activity over sensorimotor cortex to control vertical cursor movement to targets at the top or bottom edge of a video screen. In subsequent sessions, the targets were replaced with the words YES and NO, and individuals used the cursor to answer spoken YES/NO questions from single- or multiple-topic question sets. They confirmed their answers through the response verification (RV) procedure, in which the word positions were switched and the question was answered again.
  
  
  RESULTS
  For 5 consecutive sessions after initial question training, individuals were asked an average of 4.0 to 4.6 questions per minute; 64% to 87% of their answers were confirmed by the RV procedure and 93% to 99% of these answers were correct. Performances for single- and multiple-topic question sets did not differ significantly.
  
  
  CONCLUSIONS
  The results indicate that (1) EEG-based cursor control can be used to answer simple questions with a high degree of accuracy, (2) attention to auditory queries and formulation of answers does not interfere with EEG-based cursor control, (3) question complexity (at least as represented by single versus multiple-topic question sets) does not noticeably affect performance, and (4) the RV procedure improves accuracy as expected. Several options for increasing the speed of communication appear promising. An EEG-based brain-computer interface could provide a new communication and control modality for people with severe motor disabilities.
authors.affiliation: Wadsworth Center, New York State Department of Health and State University of New York, Albany 12201-0509, USA.
authors.forename: L A
authors.initials: LA
authors.lastname: Miner
authors.forename: D J
authors.initials: DJ
authors.lastname: McFarland
authors.forename: J R
authors.initials: JR
authors.lastname: Wolpaw
mesh_terms: D000328:Adult; D000368:Aged; D001288:Attention / Q000502:physiology*; D001676:Biofeedback, Psychology / Q000502:physiology*; D001931:Brain Mapping / Q000295:instrumentation; D003143:Communication Devices for People with Disabilities; D003199:Computer Systems; D006233:Persons with Disabilities / Q000534:rehabilitation*; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012984:Software; D013003:Somatosensory Cortex / Q000503:physiopathology*; D014584:User-Computer Interface