arXiv AI By Jaedong Hwang

Sensor Geometry as a Flow-Matching Prior for Multi-Channel Brain Signals

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arXiv Machine Learning
Oct 8

DenoFlow: Flow Matching for SSVEP Denoising under Real Physiological Artifacts

DenoFlow introduces a flow‑matching approach to denoise steady‑state visual evoked potential (SSVEP) EEG signals, avoiding direct mapping from noisy to clean data. It uses a field network that predicts the velocity of a straight path between contaminated and clean trials, integrating this field to produce denoised outputs while simultaneously training a classifier to supervise the result. Experiments on two public SSVEP datasets demonstrate that DenoFlow surpasses seven baseline denoising models in both signal fidelity and downstream decoding accuracy.

By Zhentao He, Ziwei Wang, Dongrui Wu