title: A method for optimizing EEG electrode number and configuration for signal acquisition in P300 speller systems.
abstract: OBJECTIVE
  The P300 speller is intended to restore communication to patients with advanced neuromuscular disorders, but clinical implementation may be hindered by several factors, including system setup, burden, and cost. Our goal was to develop a method that can overcome these barriers by optimizing EEG electrode number and placement for P300 studies within a population of subjects.
  
  
  METHODS
  A Gibbs sampling method was developed to find the optimal electrode configuration given a set of P300 speller data. The method was tested on a set of data from 15 healthy subjects using an established 32-electrode pattern. Resulting electrode configurations were then validated using online prospective testing with a naïve Bayes classifier in 15 additional healthy subjects.
  
  
  RESULTS
  The method yielded a set of four posterior electrodes (PO₈, PO₇, POZ, CPZ), which produced results that are likely sufficient to be clinically effective. In online prospective validation testing, no significant difference was found between subjects' performances using the reduced and the full electrode configurations.
  
  
  CONCLUSIONS
  The proposed method can find reduced sets of electrodes within a subject population without reducing performance.
  
  
  CONCLUSIONS
  Reducing the number of channels may reduce costs, set-up time, signal bandwidth, and computation requirements for practical online P300 speller implementation.
authors.affiliation: University of California, Los Angeles, Department of Bioengineering, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; University of California, Los Angeles, Medical Imaging Informatics Group, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
authors.forename: William
authors.initials: W
authors.lastname: Speier
authors.affiliation: University of California, Los Angeles, Department of Bioengineering, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
authors.forename: Aniket
authors.initials: A
authors.lastname: Deshpande
authors.affiliation: University of California, Los Angeles, Department of Bioengineering, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; University of California, Los Angeles, Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; University of California, Los Angeles, Interdepartmental Program in Neuroscience, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; University of California, Los Angeles, Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. Electronic address: npouratian@mednet.ucla.edu.
authors.forename: Nader
authors.initials: N
authors.lastname: Pouratian
mesh_terms: D000328:Adult; D062207:Brain-Computer Interfaces / Q000191:economics; D004566:Electrodes / Q000191:economics; D004569:Electroencephalography / Q000191:economics / Q000295:instrumentation / Q000379:methods*; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D011446:Prospective Studies; D011597:Psychomotor Performance / Q000502:physiology; D055815:Young Adult
keywords: Brain–computer interface; Electrode placement; Event-related potential; Natural language processing; P300; Speller