02392nas a2200361   4500008004100000022001400041245008900055210006900144260001200213300001600225490000800241520135100249653003401600653002901634653002501663653002901688653000901717653001901726100001601745700002001761700001701781700001901798700001301817700001901830700001401849700001501863700002301878700002401901700002101925700002101946700001501967856004801982       2008                        eng d  a1388-245700aA P300-based brain-computer interface for people with amyotrophic lateral sclerosis.0 aP300based braincomputer interface for people with amyotrophic la  c08/2008  a1909–19160 v1193 aOBJECTIVE:
The current study evaluates the efficacy of a P300-based brain-computer interface (BCI) communication device for individuals with advanced ALS.
METHODS:
Participants attended to one cell of a N x N matrix while the N rows and N columns flashed randomly. Each cell of the matrix contained one character. Every flash of an attended character served as a rare event in an oddball sequence and elicited a P300 response. Classification coefficients derived using a stepwise linear discriminant function were applied to the data after each set of flashes. The character receiving the highest discriminant score was presented as feedback.
RESULTS:
In Phase I, six participants used a 6 x 6 matrix on 12 separate days with a mean rate of 1.2 selections/min and mean online and offline accuracies of 62% and 82%, respectively. In Phase II, four participants used either a 6 x 6 or a 7 x 7 matrix to produce novel and spontaneous statements with a mean online rate of 2.1 selections/min and online accuracy of 79%. The amplitude and latency of the P300 remained stable over 40 weeks.
CONCLUSIONS:
Participants could communicate with the P300-based BCI and performance was stable over many months.
SIGNIFICANCE:
BCIs could provide an alternative communication and control technology in the daily lives of people severely disabled by ALS.10aAmyotrophic Lateral Sclerosis10abrain-computer interface10aelectroencephalogram10aevent-related potentials10aP30010aRehabilitation1 aNijboer, F.1 aSellers, E., W.1 aMellinger, J1 aJordan, M., A.1 aMatuz, T1 aFurdea, Adrian1 aHalder, S1 aMochty, U.1 aKrusienski, D., J.1 aVaughan, Theresa, M1 aWolpaw, Jonathan1 aBirbaumer, Niels1 aKübler, A  uhttp://www.ncbi.nlm.nih.gov/pubmed/1857198402016nas a2200265   4500008004100000022001400041245013800055210006900193260001200262300001400274490000700288520114400295653003401439653002901473653002501502653002901527653000901556653001901565100002201584700002501606700002601631700002401657700002101681856004801702       2006                        eng d  a0301-051100aA P300 event-related potential brain-computer interface (BCI): the effects of matrix size and inter stimulus interval on performance.0 aP300 eventrelated potential braincomputer interface BCI the effe  c10/2006  a242–2520 v733 aWe describe a study designed to assess properties of a P300 brain-computer interface (BCI). The BCI presents the user with a matrix containing letters and numbers. The user attends to a character to be communicated and the rows and columns of the matrix briefly intensify. Each time the attended character is intensified it serves as a rare event in an oddball sequence and it elicits a P300 response. The BCI works by detecting which character elicited a P300 response. We manipulated the size of the character matrix (either 3 x 3 or 6 x 6) and the duration of the inter stimulus interval (ISI) between intensifications (either 175 or 350 ms). Online accuracy was highest for the 3 x 3 matrix 175-ms ISI condition, while bit rate was highest for the 6 x 6 matrix 175-ms ISI condition. Average accuracy in the best condition for each subject was 88%. P300 amplitude was significantly greater for the attended stimulus and for the 6 x 6 matrix. This work demonstrates that matrix size and ISI are important variables to consider when optimizing a BCI system for individual users and that a P300-BCI can be used for effective communication.10aAmyotrophic Lateral Sclerosis10abrain-computer interface10aelectroencephalogram10aevent-related potentials10aP30010aRehabilitation1 aSellers, Eric, W.1 aKrusienski, Dean, J.1 aMcFarland, Dennis, J.1 aVaughan, Theresa, M1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/1686092002517nas a2200241   4500008004100000022001400041245007400055210006900129260001200198300001600210490000800226520179400234653001302028653002902041653002502070653001902095653001902114100002302133700002602156700002402182700002102206856004802227       2003                        eng d  a1388-245700aEMG contamination of EEG: spectral and topographical characteristics.0 aEMG contamination of EEG spectral and topographical characterist  c09/2003  a1580–15930 v1143 aOBJECTIVE:
Electromyogram (EMG) contamination is often a problem in electroencephalogram (EEG) recording, particularly, for those applications such as EEG-based brain-computer interfaces that rely on automated measurements of EEG features. As an essential prelude to developing methods for recognizing and eliminating EMG contamination of EEG, this study defines the spectral and topographical characteristics of frontalis and temporalis muscle EMG over the entire scalp. It describes both average data and the range of individual differences.
METHODS:
In 25 healthy adults, signals from 64 scalp and 4 facial locations were recorded during relaxation and during defined (15, 30, or 70% of maximum) contractions of frontalis or temporalis muscles.
RESULTS:
In the average data, EMG had a broad frequency distribution from 0 to >200 Hz. Amplitude was greatest at 20-30 Hz frontally and 40-80 Hz temporally. Temporalis spectra also showed a smaller peak around 20 Hz. These spectral components attenuated and broadened centrally. Even with weak (15%) contraction, EMG was detectable (P<0.001) near the vertex at frequencies >12 Hz in the average data and >8 Hz in some individuals.
CONCLUSIONS:
Frontalis or temporalis muscle EMG recorded from the scalp has spectral and topographical features that vary substantially across individuals. EMG spectra often have peaks in the beta frequency range that resemble EEG beta peaks.
SIGNIFICANCE:
While EMG contamination is greatest at the periphery of the scalp near the active muscles, even weak contractions can produce EMG that obscures or mimics EEG alpha, mu, or beta rhythms over the entire scalp. Recognition and elimination of this contamination is likely to require recording from an appropriate set of peripheral scalp locations.10aartifact10abrain-computer interface10aelectroencephalogram10aelectromyogram10aRehabilitation1 aGoncharova, I., I.1 aMcFarland, Dennis, J.1 aVaughan, Theresa, M1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/12948787