Abstract
A reference is required to record electroencephalography (EEG) signals, and therefore the reference signal can effect any quantitative EEG analysis. In this study, we investigate the impact of reference signal amplitude on a commonly used quantitative measure of the EEG, the signal energy. We show that: (i) when the reference signal and the non-referential signal have negative correlation, the energy of the referential signal will monotonically increase as the amplitude of the reference signal increases from 0 to ∞. (ii) When the reference signal and the non-referential signal have positive correlation, energy of the referential signal first decreases to some nonnegative value and then increases as the amplitude of the reference signal increases from 0 to ∞. In general, the reference signal may decrease or increase energy values. But a reference signal with higher relative amplitude will surely increase energy values. In [1], we developed a method to identify and extract the reference signal contribution to EEG recordings. Here we apply this approach to referential EEG recorded from human subjects and directly investigate the contribution of recording reference on energy and show that the reference signal may have a significant effect on energy values.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hu, S., Stead, S.M., Worrell, G.A.: Automatic identification and removal of scalp reference signal for intracranial EEGs based on independent component analysis. IEEE Trans. on Biomedical Engineering 54, 1560–1572 (2007)
Mormann, F., Andrzejak, R.G., Elger, C.E., Lehnertz, K.: Seizure prediction: the long and winding road. Brain 130, 314–333 (2007)
Esteller, R., Echauz, J., D’Alessandro, M., Worrell, G.A., Cranstoun, S., Vachtsevanos, G., Litt, B.: Continuous energy variation during the seizure cycle: towards an on-line accumulated energy. Clin. Neurophysiol. 116, 517–526 (2005)
Harrison, M.A., Frei, M.G., Osorio, I.: Accumulated energy revisited. Clin. Neurophysiol. 116, 527–531 (2005)
Gigola, S., Ortiz, F., D’Attellis, C.E., Silva, W., Kochen, S.: Prediction of epileptic seizures using accumulated energy in a multiresolution framework. J. Neurosci. Methods 138, 107–111 (2004)
Direito, B., Dourado, A., Vieira, M., Sales, F.: Combining energy and wavelet transform for epileptic seizure prediction in an advanced computational system. In: 2008 International Conference on BioMedical Engineering and Informatics, pp. 380–385 (2008)
Schiff, S.J.: Dangerous Phase. Neuroinformatics 3, 315–318 (2006)
Zaveri, H.P., Duckrow, R.B., Spencer, S.S.: On the use of bipolar montages for time-series analysis of intracranial electroencephalograms. Clin. Neurophysiol. 117, 2102–2108 (2006)
Hyvarinen, A., Oja, E.: Independent component analysis: algorithms and applications. Neural Networks 12, 411–430 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hu, S., Stead, M., Liang, H., Worrell, G.A. (2009). Reference Signal Impact on EEG Energy. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_66
Download citation
DOI: https://doi.org/10.1007/978-3-642-01513-7_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01512-0
Online ISBN: 978-3-642-01513-7
eBook Packages: Computer ScienceComputer Science (R0)