Project 2012: Unspoken Speech Detection Using a Brain-Computer Interface

 

 

 

 

 

Results:

  1. The three second/four note rhythm more quickly and accurately determined the intended letter than the two second /three note rhythm by a considerable margin.  This was the reason why the second rhythm was used in the multi-subject determination of time to detect the word “AFTER”.   The three second rhythm created my significantly unique waveforms for each letter depicted and was used as the rhythm for the detection of letters with 5 test subjects.
  2. The rate of spelling a five letter work using the non-invasive ADS11298/Arduino EEG system described here was found to be an average of 39.3 seconds with a standard deviation of 2.0 seconds for all of the test results (18 data points).  Note that two subjects were each unable to finish spelling the test word in one of their trials.  This is a significant improvement over the P-300 Speller system which has been tested many times, but is known to have a speed of 105 seconds for a 5 letter work (Usakli, 2009).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 Conclusions:

  1. The ADS1298/Arduino EEG system was successful in generating useful signals for the selective detection of letters.
  2. A three second/four note rhythm was found to be significantly superior to a two second/three note rhythm for signal differentiation.
  3. The novel combination of a three second/four note rhythm imagined by the test subject, coupled with LDA classification and sorting by Bayes classifiers designed for this experiment was successful in communicating silently.
  4. The time taken for the subject to communicate a 5 letter word was 39.3 seconds with a standard deviation of 2.0 seconds in 18 of the 20 test subject sessions.
  5. The designed ADS1298/Arduino EEG system non-invasively classifying a four note, three second signal was found to be significantly faster than the existing P300 Speller System.