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/library/oar/handle/123456789/18639Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Camilleri, Tracey A. | |
| dc.contributor.author | Camilleri, Kenneth P. | |
| dc.contributor.author | Fabri, Simon G. | |
| dc.date.accessioned | 2017-04-26T11:35:25Z | |
| dc.date.available | 2017-04-26T11:35:25Z | |
| dc.date.issued | 2014 | |
| dc.identifier.citation | Camilleri, T. A., Camilleri, K. P., & Fabri, S. G. (2014). Automatic detection of spindles and K-complexes in sleep EEG using switching multiple models. Biomedical Signal Processing and Control, 10, 117-127. | en_GB |
| dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/18639 | |
| dc.description.abstract | This work investigates the use of switching linear Gaussian state space models for the segmentation and automatic labelling of Stage 2 sleep EEG data characterised by spindles and K-complexes. The advan- tage of this approach is that it offers a unified framework of detecting multiple transient events within background EEG data. Specifically for the identification of background EEG, spindles and K-complexes, a true positive rate (false positive rate) of 76.04% (33.47%), 83.49% (47.26%) and 52.02% (7.73%) respectively was obtained on a sample by sample basis. A novel semi-supervised model allocation approach is also proposed, allowing new unknown modes to be learnt in real time. | en_GB |
| dc.language.iso | en | en_GB |
| dc.publisher | Elsevier Ltd. | en_GB |
| dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
| dc.subject | Electroencephalography | en_GB |
| dc.subject | Sleep -- Stages | en_GB |
| dc.subject | Sleep -- Stages -- Measurement -- Data processing | en_GB |
| dc.title | Automatic detection of spindles and K-complexes in sleep EEG using switching multiple models | en_GB |
| dc.type | article | en_GB |
| dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
| dc.description.reviewed | peer-reviewed | en_GB |
| dc.identifier.doi | 10.1016/j.bspc.2014.01.010 | |
| Appears in Collections: | Scholarly Works - FacEngSCE | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Automatic detection of spindles and K-complexes in sleep EEG using switching multiple models.pdf Restricted Access | 1.4 MB | Adobe PDF | View/Open Request a copy |
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