Fractal dimension based neurofeedback in serious games

EEG-based technology is widely used in serious game design since more wireless headsets that meet consumer criteria for wearability, price, portability, and ease-of-use are coming to the market. Originally, such technologies were mostly used in different medical applications, Brain Computer Interfaces (BCI) and neurofeedback games. The algorithms adopted in such applications are mainly based on power spectrum analysis, which may not be fully revealing the nonlinear complexity of the brain activities. In this paper, we first review neurofeedback games, EEG processing methods, and algorithms, and then propose a new nonlinear fractal dimension based approach to neurofeedback implementation targeting EEG-based serious games design. Only one channel is used in the proposed concentration quantification algorithm. The developed method was compared with other methods used for the concentration level recognition in neurofeedback games. The result analysis demonstrated an efficiency of the proposed approach. We designed and implemented new EEG-based 2D and 3D neurofeedback games that make the process of brain training more enjoyable.

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