Application of adaptive filtering to steady-state evoked response
A new method to detect steady-state evoked potentials (EPs) is presented. The technique is based on a two-weight recursive least squares (RLS) adaptive filter and the T circ 2 statistic. Simulations with known sinusoids buried in Gaussian noise and in EEG noise indicate that the adaptive filter can detect signals at 3 or 4 times lower signal-to-noise ratios that the discrete Fourier transform (DFT). Qualitatively similar results were obtained with human visual evoked potential recordings.
KeywordsAdaptive filtering Recursive least squares method Steady-state evoked potentials Visual evoked potentials (VEPs)
Unable to display preview. Download preview PDF.
- Eizenmann, M., McCulloch, D., Hui, R., andSkarf, B. (1989): ‘Detection of threshold visual evoked potentials (VEPs),’Noninvasive Assessment of the Visual System,7, pp. 88–91Google Scholar
- Glover, G. (1975): ‘Adaptive noise cancelling of sinusoidal interferences’. PhD dissertation, Stanford University, USAGoogle Scholar
- Orfanidis, S. J. (1988): ‘Optimum signal processing: an introduction’ (Macmillan, New York)Google Scholar
- Regan, D. (1989): ‘Human brain electrophysiology: evoked potentials and evoked magnetic fields in science and medicine’ (Elsevier, New York)Google Scholar
- Tang, Y., andNorcia, A. M. (1993): ‘An adaptive filter for steadystate evoked potentials,’Proc. 15th Annual International Conference of IEEE EMBS, San Diego, California, vol. 15, pp. 322–323Google Scholar
- Widrow, B.,et al. (1975): ‘Adaptive noise cancelling: principles and applications,’Proc. IEEE,63, pp. 1697–1716Google Scholar