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

Area of Science:

• Biophysics
• Neuroscience
• Biomedical Engineering

Background:

• Optically pumped magnetometer-based magnetoencephalography (OPM-MEG) offers advantages over traditional systems, such as flexibility and no need for cryogenic cooling.
• OPM-MEG is highly sensitive to external magnetic field fluctuations, making it susceptible to motion artifacts.
• Head movements during OPM-MEG recordings can introduce significant noise, compromising data quality.

Purpose of the Study:

• To develop and evaluate a novel method for suppressing head motion artifacts in OPM-MEG.
• To enhance the signal quality and robustness of OPM-MEG recordings in the presence of motion.
• To improve the reliability of OPM-MEG for research and clinical applications.

Main Methods:

• An Adaptive Time-varying (ATH) Homogeneous field correction (HFC) method was proposed.
• The ATH-HFC method integrates time-varying HFC with adaptive filtering to estimate and correct for magnetic field fluctuations caused by head movements.
• Filter parameters are dynamically adjusted to minimize discrepancies between measured and predicted background fields.

Main Results:

• The ATH method demonstrated effectiveness in simulation studies.
• Experiments involving median nerve stimulation in OPM-MEG confirmed the method's ability to enhance signal quality.
• The ATH method showed robustness across various experimental conditions, significantly reducing motion artifacts.

Conclusions:

• The ATH-HFC method provides an effective solution for motion artifact suppression in OPM-MEG.
• The robustness of the ATH method supports its broader application in both research and clinical settings.
• This technique advances the utility of OPM-MEG by improving data reliability in the face of motion-related interference.