2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, Vol.2006, p.1323-1326
2006
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- Autor(en) / Beteiligte
- Titel
- An Evaluation of Autoregressive Spectral Estimation Model Order for Brain-Computer Interface Applications
- Ist Teil von
- 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, Vol.2006, p.1323-1326
- Ort / Verlag
- United States: IEEE
- Erscheinungsjahr
- 2006
- Quelle
- IEEE Xplore
- Beschreibungen/Notizen
- Autoregressive (AR) spectral estimation is a popular method for modeling the electroencephalogram (EEG), and therefore the frequency domain EEG phenomena that are used for control of a brain-computer interface (BCI). Several studies have been conducted to evaluate the optimal AR model order for EEG, but the criteria used in these studies does not necessarily equate to the optimal AR model order for sensorimotor rhythm (SMR)-based BCI control applications. The present study confirms this by evaluating the EEG spectra of data obtained during control of SMR-BCI using different AR model orders and model evaluation criteria. The results indicate that the AR model order that optimizes SMR-BCI control performance is generally higher than the model orders that are frequently used in SMR-BCI studies
- Sprache
- Englisch
- Identifikatoren
- ISBN: 9781424400324, 1424400325ISSN: 1557-170XDOI: 10.1109/IEMBS.2006.259822Titel-ID: cdi_proquest_miscellaneous_68350869
- Format
- –
- Schlagworte
- Algorithms, Artificial Intelligence, Band pass filters, Brain computer interfaces, Brain Mapping - methods, Brain modeling, Cities and towns, Communication system control, Computer Simulation, Electroencephalography, Electroencephalography - methods, Filtering, Frequency estimation, Humans, Models, Neurological, Models, Statistical, Pattern Recognition, Automated - methods, Regression Analysis, Reproducibility of Results, Rhythm, Sensitivity and Specificity, USA Councils, User-Computer Interface