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A collaborative filtering approach for quasi-brain-death EEG analysis
Y. Xia, L.Li, J. Cao, M. Golz, and D. P. Mandic
In Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, pages 182-196. IEEE Society, IEEE Press, May 2011 [doi].Abstract
Evaluating the significance differences between the group of comatose patients and the group of brain death is important in the detection of brain death. This paper presents a novel method for the discrimination between discrete states of brain consciousness. Based on a collaborative adaptive filtering ar- chitecture using a convex combination of two heterogeneous adaptive filters, the evolution of the mixing parameter can be used as an indicator of the fundamental signal nature of different EEG recordings. Simulations illustrate the suitabil- ity of this approach to differentiate between the coma and quasi-brain-death states.
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@inproceedings{3181,
author = {Y. Xia and L.Li and J. Cao and M. Golz and D. P. Mandic},
title = {A collaborative filtering approach for quasi-brain-death {EEG} analysis},
month = {May},
year = {2011},
pages = {182-196},
keywords = {determinacy analysis, Craig interpolants},
note = {},
doi = {10.1109/ICASSP.2011.5946486},
url = {http://www.cs.kent.ac.uk/pubs/2011/3181},
publication_type = {inproceedings},
submission_id = {5608_1320780477},
ISBN = {978-1-4577-0538-0},
booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on},
organization = {IEEE Society},
publisher = {IEEE Press},
ISSN = {1520-6149},
}