The project is inspired by Neuralink & TheBCIGuys and will be a major impact in the field of Brain Computer Interfaces. This platform utilises the data received from invasive/non-invasive technologies to perform real time brain diagnosis via the use of machine learning.
Machine learning models of various brain states will be developed via pattern recognition in EEG recordings and used as a base to improve the current diagnostics of the clinical practice.
The short term goal of the project is to develop accurate models to determine if the patient suffers from depression, epilepsy or schizophrenia.
The long term goal of the project is to integrate real time data to perform predictions from existing or newly developed models to determine if the host is suffering from an episode of schizophrenia or various other vital health defects such as stroke. With effective models in place a guardian will be able to view the brain state of the host and therefore protect them when they are most vulnerable.
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