Employing a Biofeedback Method Based on Hemispheric Synchronization in Effective Learning

  • K. Kaszuba
  • B. Kostek
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 99)

Abstract

The following Chapter presents a new approach to effective learning by employing a biofeedback method based on hemispherical synchronization. The application proposed uses a wireless EEG (electroencephalography) recording system of the user’s brain waves and powerful signal processing and classification to produce a reliable feedback. Alpha and beta brain rhythms are analyzed by applying DWT (Discrete Wavelet Transform) and by calculating the statistics for each analyzed window. EOG (electrooculogram) artifacts are eliminated from the signal through adaptive filtration in the time-frequency domain. Three different learning methods are implemented in the proposed application: mind map, flash cards and non-linear notes. Several tests are performed with the users. Based on the brain feedback information and the user’s learning profile test results, an optimized learning method is chosen for an individual user. Information about hemispherical synchronization provides vital information for system adjustments. The results obtained show a difference between traditional learning and one using a feedback loop, indicating that synchronized hemispheres improve learning abilities. In conclusion the critical evaluation of the method is given.

Keywords

Discrete Wavelet Transform Adaptive Filtration Synchronization State Learning Profile Stationary Wavelet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • K. Kaszuba
    • 1
  • B. Kostek
    • 1
  1. 1.Multimedia Systems DepartmentGdansk University of TechnologyGdanskPL

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