Project DetailsBrain-Computer Interface (BCI) is a fast-growing field in electrical engineering with many different applications. Neural researchers found different kinds of hierarchies in the brain, and in this work, we tried to exploit them. By embedding data into the Hyperbolic Manifold, we get a continuous tree-like data structure and thus can store hierarchical properties efficiently. In our project, we tried to use Machine Learning (ML) and Deep Learning (DL) techniques to embed EEG signals in hyperbolic space. After that, we tried to use the embedded data to solve classification problems. Although the initial results seemed promising, we couldnt get too good results after all.
We will further discuss this in the method and discussion sections. Even though, because of the theoretical justifications, we believe that the
method can yield good results with more work and larger datasets.
