Online removal method for nuclear magnetic artifacts in synchronous EEG-fMRI data acquisition

Abstract

The invention discloses an online removal method for nuclear magnetic artifacts in synchronous EEG-fMRI data acquisition. The online removal method comprises the following steps that (1), pulse artifacts are filtered from acquired noise-containing electroencephalogram signals through a low-pass filter with designed parameters; (2), up-sampling is carried out on the filtered signal in the step (1), and the electroencephalogram signals with a mark sent by fMRI equipment are synchronized, namely synchronizing is carried out by using a synchronization box to obtain a signal Sh; and (3), the electroencephalogram signals are random signals, the gradient noise takes a slice scanning time T as a period, and the shape of the noise in each period is similar, so that a sliding window is constructed by using N slices to construct a gradient noise formwork. The adaptive SVD denoising used in the method considers the morphological characteristics of the electrocardiographic artifacts, so that the signal-to-noise ratio of the collected signal is better improved; and compared with PCA-based OBS denoising, the denoising method has the advantages that the effective electroencephalogram signals are better reserved while the artifacts are removed, and the accuracy is higher.

Description

technical field [0001] The invention belongs to the technical field of brain signal processing, and in particular relates to an online method for removing nuclear magnetic artifacts in synchronous EEG-fMRI data acquisition. Background technique [0002] With growing interest in combining physiological EEG and hemodynamic measurements in functional neuroimaging, there has been steady development in data acquisition techniques for simultaneous EEG-fMRI. EEG signals have the characteristics of high time resolution and low spatial resolution, while MRI has the characteristics of low time resolution and high spatial resolution, so the combination of EEG signals and MRI is very important for the study of brain function and spirit. It is of great significance to study the pathogenesis and cognition of similar diseases. [0003] However, in simultaneous EEG-fMRI experiments, the acquired EEG signals will be overwhelmed by huge noise due to the high-intensity magnetic field transfor...

AI Technical Summary

Problems solved by technology

[0009] In the above-mentioned existing technologies for removing nuclear magnetic artifacts, the functions realized are only to shield noise signals through hardware or to perform offline denoising through algorithms, but fail to perform synchronous real-time denoising through signal denoising algorithms.

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