Signal subspace integration for improved seizure localization.
A subspace signal processing approach is proposed for improved scalp EEG-based localization of broad-focus epileptic seizures, and estimation of the directions of source arrivals (DOA). Ictal scalp EEGs from adult and pediatric patients with broad-focus seizures were first decomposed into dominant signal modes, and signal and noise subspaces at each modal frequency, to improve the signal-to-noise ratio while preserving the original data correlation structure. Transformed (focused) modal signals were then resynthesized into wideband signals from which the number of sources and DOA were estimated. These were compared to denoised signals via principal components analysis (PCA). Coherent subspace processing performed better than PCA, significantly improved the localization of ictal EEGs and the estimation of distinct sources and corresponding DOAs.
Department of Radiology, Children’s Hospital Boston and Harvard Medical School, Boston, MA 02115, USA. caterina@mit.edu
Catherine
C
Stamoulis
Iván Sánchez
IS
Fernández
Bernard S
BS
Chang
Tobias
T
Loddenkemper
D000293:Adolescent; D000328:Adult; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012640:Seizures / Q000503:physiopathology*; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D055815:Young Adult