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Asynchronous Brain Computer Interface using Hidden Semi-Markov Models

Oliver, Gareth; Sunehag, Peter; Gedeon, Tamas (Tom)


Ideal Brain Computer Interfaces need to perform asynchronously and at real time. We propose Hidden Semi-Markov Models(HSMM) to better segment and classify EEG data. The proposed HSMM method was tested against a simple windowed method on standard datasets. We found that our HSMM outperformed the simple windowed method. Furthermore, due to the computational demands of the algorithm, we adapted the HSMM algorithm to an online setting and demonstrate that this faster version of the algorithm can...[Show more]

CollectionsANU Research Publications
Date published: 2012
Type: Conference paper
Source: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
DOI: 10.1109/EMBC.2012.6346528


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