Classification of Scalp EEG Scans into Different Cognitive Brain States
We usually find it hard to adjust our brain states between concentration and relaxation, its flexibility that we cannot have easily. Therefore, a convenient and real-time concentration-relaxation feedback system should be established so as to show our current brain state and help us adjust our brain state in a more flexible manner. In our research, we attempt to find and establish the effect of stimulus over human brain and determine ways to initiate concentration and relaxation.
Workflow
- We collect and analyze EEG for different Brain states such as relaxed, Concentrated, Stressed.
- The Machine Learning model is trained over this data so that it can classify new EEG recordings under these classes
- The subject is introduced to a different stimulus of music and videos and the change in brain state is recorded due to the stimulus
- When the required change in the brain state is achieved the stimulus properties are saved for that particular subject and tested on different users to validate.
- If the desired results are achieved the stimulus can be considered a viable option for transferring to a particular brain state
Knowledge Gained
- Cognitive information provided by EEG signals
- The relevance of constituent Alpha, Beta, Gamma, Theta and delta waves for determining brain state
- The relation between audio and visual stimulus over brain state.