Abstract：
:A method for the estimation of medium rate transitions of non-stationary electroencephalograms (EEG) is proposed. The method is applicable to such EEG dynamics that are between (a) fast transitions for which segmentation procedures are used and (b) slow transitions for which adaptive filters work properly. The estimation of the transition dynamics is based on a novel time-varying autoregressive model. This model belongs to the class of deterministic regression time-varying autoregressive models and its parametrisation allows only simultaneous transitions in all coefficient evolutions. Data from 22 patients was analysed. The performance of the method is first evaluated with realistic simulations of known transition dynamics and it is shown to be able to track medium-rate transitions. The method is then applied to the estimation of the dynamics of event related desynchronisation. It is shown that the proposed method is able to estimate the transitions which are less apparent, such as from a multi-infarct patient.
journal_name
Med Biol Eng Computjournal_title
Medical & biological engineering & computingauthors
Hiltunen JK,Karjalainen PA,Partanen J,Kaipio JPdoi
10.1007/BF02513305keywords:
subject
Has Abstractpub_date
1999-05-01 00:00:00pages
309-15issue
3eissn
0140-0118issn
1741-0444journal_volume
37pub_type
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