Method for automatically recogniting and eliminating ophthalmogyric interference in electroencephalo-signals

Abstract

A method for automatically recognizing and eliminating the eye moving interference from electroencephalogram (EEG) includes such steps as extracting the components from EEG by ICA, dipole locating analyzing, creating a bipole position distribution model about eye moving interference, and ICA reverse transformation to automatically eliminate said interference.

Description

technical field [0001] The invention relates to biomedical signal processing technology, in particular to a method for automatically identifying and eliminating eye movement interference in brain electrical signals. Background technique [0002] At present, there are new research results emerging in the field of EEG signal processing technology at home and abroad, and these achievements play an important role in medical research and clinical practice. Clinical electroencephalography (EEG) is the spontaneous and rhythmic electrical activity of brain nerve cell groups recorded by electrodes, and has become a routine and powerful tool for medical clinical brain disease diagnosis and observation of brain function. At present, EEG research is very active. On the one hand, it is clinical EEG research, which is of great significance to the identification, disease prediction, diagnosis and treatment of brain diseases; on the other hand, it is the study of brain function and cognitio...

AI Technical Summary

Problems solved by technology

The regression method needs to record oculoelectricity (EOG) as a reference at the same time. Since the recorded oculoelectricity will contain EEG components, some EEG components will inevitably be removed when eliminating eye movement interference; the PCA method decomposes the signal into The disadvantage of the components orthogonal to each other is that the complete separation of eye movement interference and EEG components with similar amplitudes cannot be achieved, and the interference and EEG components do not necessarily have an orthogonal relationship

Although Independent Component Analysis (ICA) can separate EEG signals and eye movement interference components, how to identify EEG slow waves and eye movement interference usually requires manual judgment by physicians, resulting in time-consuming denoising work and lack of objectivity, failure to automate

Images