Wavelet transforms are used to analyze electroencephalographic data recorded from individual subdural electrodes and 2D electrode grids in direct contact with the brain. Surrogate data techniques are used to filter noise and resolve structure in the data. Spike and seizure detection from individual electrodes with wavelet transforms are compared with windowed Fourier transforms. Wavelet transforms are a powerful means to identify epileptiform activity such as spikes from such data and also offer a method to localize the foci of epileptic seizures from electrode grids.
All Science Journal Classification (ASJC) codes
- Atomic and Molecular Physics, and Optics