Determination of the Time-frequency Features for Impulse Components in EEG Signals.

ABSTRACT: Accurately identifying the timing and frequency characteristics of impulse components in EEG signals is essential but limited by the Heisenberg uncertainty principle. Inspired by the visual system's ability to identify objects and their locations, we propose a new method that integrates a visual system model with wavelet analysis to calculate both time and frequency features of local impulses in EEG signals. We develop a mathematical model based on invariant pattern recognition by the visual system, combined with wavelet analysis using Krawtchouk functions as the mother wavelet. Our method precisely identifies the localization and frequency characteristics of the impulse components in EEG signals. Tested on task-related EEG data, it accurately detected blink components (0.5 to 1 Hz) and se

SUBMITTER: Filimonova N 

PROVIDER: S-EPMC11757888 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature