Motion artifact suppression method based on adaptive time-varying homogeneous field correction for OPM-MEG

Objective. Optically pumped magnetometer-based magnetoencephalography (OPM-MEG) offers significant advantages over traditional systems based on superconducting quantum interference devices, including flexibility and the ability to record brain activity without cryogenic cooling. However, OPM-MEG is highly susceptible to motion artifacts due to its sensitivity to external magnetic field fluctuations. Approach. To address this challenge, we propose an Adaptive Time-varying (ATH) Homogeneous field correction (HFC) method, which integrates time-varying HFC with adaptive filtering to suppress head motion artifacts. The ATH method estimates background magnetic field components induced by head movements and dynamically adjusts filter parameters to minimize discrepancies between measured signals and predicted background fields. Main results. We evaluated the ATH method through simulation studies and median nerve stimulation OPM-MEG experiments, demonstrating its effectiveness in enhancing signal quality and robustness across various experimental conditions. Significance. ATH offers an effective solution for motion artifact suppression in OPM-MEG systems. Its robustness under diverse conditions supports broader application in research and clinical settings.