@inproceedings{97a2030148194da48c41bbdc2b9f9bff,
title = "A framework of adaptive brain computer interfaces",
abstract = "Stationarity is often found in session-to-session transfers of Brain Computer Interfaces (BCIs). To cope with the problem, a framework based on Common Spatial Patterns (CSP), Linear Discriminant Analysis (LDA), and covariate shift adaptation methods is proposed. Covariate shift adaptation is an effective method which can adapt to the testing sessions without the need for labeling the testing session data. This framework has been applied on one electrocorticogram (ECoG) dataset and one Electroencephalogram (EEG) dataset from BCI Competition III. Despite the different characteristics of ECoG and EEG, non-stationarity appeared in both datasets. Results showed that the proposed framework compares favorably with those methods used in the BCI Competition, revealing the effectiveness of covariate shift adaptation in tackling the nonstationarity in Brain Computer Interfaces.",
keywords = "Adaptive brain-computer interface, Covariate shift, ECoG, EEG",
author = "Yan Li and Yasuharu Koike and Masashi Sugiyama",
year = "2009",
doi = "10.1109/BMEI.2009.5305646",
language = "英语",
isbn = "9781424441341",
series = "Proceedings of the 2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009",
booktitle = "Proceedings of the 2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009",
note = "2009 2nd International Conference on Biomedical Engineering and Informatics, BMEI 2009 ; Conference date: 17-10-2009 Through 19-10-2009",
}