Artifact Suppression in OPM-MEG for Parkinson's Disease Patients with DBS Implants Using Oblique Projection-Based Extended Homogeneous Field Correction

Deep brain stimulation (DBS) is a critical neuromodulation technique that has been widely applied in the treatment of neurological disorders such as Parkinson's disease (PD) and epilepsy. As an important functional neuroimaging modality, magnetoencephalography (MEG) has played a key role in DBS research. In particular, the next-generation MEG based on optically pumped magnetometers (OPM-MEG), offers greater potential for clinical applications. However, the strong electromagnetic interference generated by DBS systems makes data acquisition and analysis challenging in OPM-MEG recordings from patients with implanted devices. To the best of our knowledge, there have been no studies that systematically investigate the characteristics or suppression of DBS-induced artifacts in OPM-MEG recordings from human subjects. In this paper, we describe a novel OPM-MEG interference suppression algorithm called extended homogeneous field correction based on oblique projection (opHFC), developed for suppressing environmental noise in OPM-MEG. To illustrate the practical application of opHFC in clinical settings, particularly for patients with DBS implants. We evaluate the performance of opHFC in denoising OPM-MEG data from PD patients with DBS implants. By applying opHFC to real-world clinical data, we assess its ability to reduce DBS-induced artifacts while preserving neural activity patterns and conduct a comprehensive comparison between opHFC and several commonly used artifact suppression techniques in OPM-MEG. Our results show that opHFC significantly enhances signal quality and achieves the most effective suppression performance, demonstrating its potential as a reliable tool for advancing OPM-MEG applications in challenging clinical environments. This study highlights the practical value of opHFC in improving OPM-MEG data quality for PD patients with DBS, paving the way for more accurate neuroscientific research and clinical diagnostics.

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Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2025-01-01
DOI
https://doi.org/10.1109/jbhi.2025.3626123
Citations
1
Primary Topic
Atomic and Subatomic Physics Research
Type
article
Field-Weighted Citation Impact
1.25
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article

Artifact Suppression in OPM-MEG for Parkinson's Disease Patients with DBS Implants Using Oblique Projection-Based Extended Homogeneous Field Correction

Yaxiang Wang, W. G. Li, Qianqian Wu, Fuzhi Cao et al.
1 citations
IEEE Journal of Biomedical and Health Informatics
Atomic and Subatomic Physics Research
1.25
article

Artifact Suppression in OPM-MEG for Parkinson's Disease Patients with DBS Implants Using Oblique Projection-Based Extended Homogeneous Field Correction

Yaxiang Wang, W. G. Li, Qianqian Wu, Fuzhi Cao, Jianzhi Yang, Min Xiang, Fulong Wang, Nan An
article en
1 citations

Abstract

Deep brain stimulation (DBS) is a critical neuromodulation technique that has been widely applied in the treatment of neurological disorders such as Parkinson's disease (PD) and epilepsy. As an important functional neuroimaging modality, magnetoencephalography (MEG) has played a key role in DBS research. In particular, the next-generation MEG based on optically pumped magnetometers (OPM-MEG), offers greater potential for clinical applications. However, the strong electromagnetic interference generated by DBS systems makes data acquisition and analysis challenging in OPM-MEG recordings from patients with implanted devices. To the best of our knowledge, there have been no studies that systematically investigate the characteristics or suppression of DBS-induced artifacts in OPM-MEG recordings from human subjects. In this paper, we describe a novel OPM-MEG interference suppression algorithm called extended homogeneous field correction based on oblique projection (opHFC), developed for suppressing environmental noise in OPM-MEG. To illustrate the practical application of opHFC in clinical settings, particularly for patients with DBS implants. We evaluate the performance of opHFC in denoising OPM-MEG data from PD patients with DBS implants. By applying opHFC to real-world clinical data, we assess its ability to reduce DBS-induced artifacts while preserving neural activity patterns and conduct a comprehensive comparison between opHFC and several commonly used artifact suppression techniques in OPM-MEG. Our results show that opHFC significantly enhances signal quality and achieves the most effective suppression performance, demonstrating its potential as a reliable tool for advancing OPM-MEG applications in challenging clinical environments. This study highlights the practical value of opHFC in improving OPM-MEG data quality for PD patients with DBS, paving the way for more accurate neuroscientific research and clinical diagnostics.

IEEE Journal of Biomedical and Health InformaticsVol. PP
Hangzhou Special Equipment Inspection and Research Institute (CN), Qilu Hospital of Shandong University (CN), Beihang University (CN)
Openalex Percentile: Top 16%
Atomic and Subatomic Physics Research
1.25
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