Mental activity type recognition with few seconds of on-going EEG
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1
IHNA RAS, Human Higher Nervous Activity Laboratory, Russia
A new method for recognition of mental task type being solved in mind is elaborated. The recognition is based on the analysis of EEG rhythms. Few seconds of EEG are enough to complete the recognition since the method utilizes an Artificial Neural Network (ANN).
Method: 240 tasks of eight different types belonging to two basic thinking modes (spatial and verbal) were presented to a subject in a random order during an experiment. A total of 30 experiments with 15 healthy adult subjects were carried out. Epochs of EEG correspondent to task solving in mind were selected, inspected for artifacts and processed. Single power spectra, i.e. square modules of Fast Fourier Transform of single EEG trials, were calculated. These spectra served as an input to ANN. A Perceptron -like ANN was utilized as a learned classifier. First, the ANN was learned to recognize the task types correctly with a set of data, whose class was known. Later, the network recognized the unknown (new) data. The average duration of single EEG trials was about 10 seconds, the minimum was 2 seconds.
Results:Two basic modes of thinking, i.e. verbal vs. spatial, were discriminated with confidence (average correct recognition score was about 90%). This meant that, being learned to recognize basic thinking classes with any four task types (two of them belonging to spatial thinking, and the other two – to verbal) the ANN then determines the basic class of other four task types correctly. The recognition of particular task types within one basic thinking class could also be performed, but with much less accuracy (about 66 % on average). Perfection of preprocessing and classification methods may lead to the improvement of recognition scores. The obtained results may be useful in some practical applications.
Conference:
Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009.
Presentation Type:
Poster Presentation
Topic:
Electrophysiology
Citation:
Naumov
R,
Ivanitsky
G and
Ivanitsky
A
(2019). Mental activity type recognition with few seconds of on-going EEG.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2009.
doi: 10.3389/conf.neuro.11.2009.08.062
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Received:
22 May 2009;
Published Online:
09 May 2019.
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Correspondence:
Roman Naumov, IHNA RAS, Human Higher Nervous Activity Laboratory, Moscow, Russia, roman.naumov@gmail.com