Project 2011: Computer-Aided Telepathic Communications

 

 

 

Conclusions:

 ·       A system of determining phonemes consistently from a two-electrode EEG was not completely successful.  The data does not support the consistent ability to read phonemes from the F7 locale in the 10-20 scheme by itself using the current system.  Some phonemes were significantly apparent in more than one band, but the system as presented cannot be used for speech as only 4 of the 6 phonemes could be adequately detected.  

 ·       What now needs to be investigated is whether individual phonemes are only significantly determined in specific frequency bands or whether they should be significant across the entire frequency spectrum known for human speech (3- 48 Hz).

 ·       Whether the use of a two-channel appliance affected the results is a matter of speculation.  Future work would need to determine whether having a 6-channel (or more) system additionally covering Wernicke’s Area, also known for higher language functions (Callies, 2006), would improve the detection of phonemes.

 ·       In this study, no attempt was made to “train” the user by giving real-time feedback to whether their thinking was matching the phoneme being detected.  The study was undertaken to find a system that does not require training, as many of the locked-in patients who need such a system would find training difficult.

 ·       The use of Fast Fourier Transformation in the pre-processing of detected signals could also be investigated.  One very positive outcome of this experiment is that scenarios were designed to acquire, train and classify brain signals in the OpenVIBE environment.  In particular, the connection to a MATLAB server developed for testing various pre-processing methods not available (e.g.  The Hilbert Huang Transform) makes future work in this area less time-consuming and more productive.

 ·       This experiment was important for determining if a simple non-invasive EEG detection device could be used for the detection of phonemes.  Such work is important in determining the requirements for building a non-invasive and inexpensive to deploy machine that allows for the non-verbal communication of unspoken speech.