The MINI-magnetically shielded room (MINI-MSR) offers a near-zero magnetic environment for the high performance of optically pumped atomic magnetometers (OPMs) in magnetoencephalography (MEG) tests. It has the advantages, such as being small-sized, portable, lightweight, offering efficient space utilization, and being cost-effective. However, owing to its small size and narrow internal space, the MINI-MSR can only provide a limited uniform region with larger gradients and irregular magnetic noise distributions. Moreover, it is affected by large external background fluctuations. Once the external interference exceeds the magnetic shielding capacity of the MINI-MSR, the precision of OPMs is compromised. Therefore, an active magnetic compensation system (AMCS) composed of biplanar coils (BCs) is introduced to enlarge the uniform region, maintaining the inhomogeneity errors below 1% to meet the measurement accuracy. However, conventional algorithms for designing BCs struggle with searching for the regularization coefficient ω that determines the coil’s shape. The process lacks ergodicity and efficiency, posing challenges in obtaining maximum volume and uniformity within the target region. In this study, a new hybrid method (NHM) composed of the target field method (TFM), image method (IM), and novel artificial fish swarm algorithm (novel ASFA) is proposed to design BCs for the AMCS. The aim is to suppress background field fluctuations, enhancing the signal-to-noise ratio while addressing coupled errors to reduce larger gradients and magnetic noise levels. Experimental results show that the maximum inhomogeneity error of BCs is less than 1.23%, which is consistent with simulation results. The sensitivity of the AMCS at 0.01 Hz ranges from 180 to 0.16 pT/Hz ^1/2 , realizing the noise suppression ratio of 30.51 dB. Based on the closed-loop AMCS, the signal-to-noise ratio in the alpha rhythm generation task is effectively improved.

Abstract-The presence of high-amplitude and specific-frequency magnetic interference in the environment can significantly degrade the signal-to-noise ratio of magnetocardiography (MCG) signal within a magnetically shielded room (MSR), thereby severely impeding the extraction of cardiac magnetic characteristic signal and hindering accurate diagnosis of heart-related diseases. The conventional linear active disturbance rejection control (LADRC) based active magnetic compensation system exhibits limited capability to counteract such interferences, resulting in inadequate suppression effects against high-amplitude and specific-frequency magnetic disturbances in the environment. To address this issue, this paper proposes an active magnetic interference compensation method (LESO-LSEF-PR) that integrates linear extended state observer (LESO), linear state error feedback control law (LSEF), and adaptive proportional resonance control (PR). Comparative analysis with LADRC control approach demonstrates that LESO-LSEF-PR offers superior attenuation performance for high-amplitude and specific-frequency magnetic interferences. Experimental results show that the LESO-LSEF-PR method proposed in this paper can reduce the average magnetic field noise within the 3~40 Hz range of the MSR from 93.05 fT/√Hz to 19.85 fT/√Hz. Compared with the traditional LADRC control method, the noise suppression effect is improved by about 29.7%.

Ischemic chronic heart failure (ICHF) that is accompanied by bundle-branch block (BBB) represents a complex cardiac electrophysiological abnormality that has a significant impact on cardiac function. Under complex pathological cardiac conditions, signal changes are often insufficiently detected. Owing to the fixed and limited number of electrode placements of the electrocardiogram (ECG) subtle, abnormal, cardiac electrophysiological signals are difficult to capture comprehensively. In contrast, magnetocardiographs (MCGs) measured by spin-exchange relaxation-free (SERF) magnetometers, with their higher sensitivity and spatial resolution, represent cardiac electrical activity more accurately. However, owing to the longer electrical-conduction pathways of the cardiac deep structure and the superimposition of abnormal signals from the BBB-accompanied ICHF, these abnormal signals are weak and capture by SERF magnetometers is difficult; precise identification of the MCG features is thus more challenging. To address these technical limitations and enhance the detection of cardiac electrophysiological abnormalities, a more precise solution is required. In this paper, a comprehensive cardiac electrophysiological-conduction model and simulation method are proposed. Conduction pathways are mathematically modeled, and their contributions to the magnetic field are calculated. Detailed images of cardiac electrical activity are obtained through interpolation of MCGs. More accurate MCG data are generated by solving the comprehensive myocardial current I’_total. Simulated MCGs provide new insights for the MCG-technology optimization and highlight the value of cardiac electrophysiological conduction models in MCG measurements, thereby significantly improving the early detection and diagnosis of BBB.

The MINI-magnetically shielded cabin (MINI-MSC) offers a near-zero magnetic environment for optically pumped atomic magnetometers (OPMs) to measure the magnetocardiography (MCG) and magnetoencephalography (MEG). However, the MINI-MSC’s confined interior and restricted uniform area make it challenging to capture high-quality bodily signals. Once the external interference surpasses the passive magnetic shielding capacity of the MINI-MSC, the volume and the homogeneity of the uniform region are reduced significantly, leading to the poor quality of the signal collected by OPMs. Therefore, an uniform active magnetic compensation system (UAMCS) composed of bi-planar coils (BCs) is introduced to suppress interference for enlarging the uniform region. The performance of the UAMCS depends on the BCs, but under finite-size ferromagnetic boundaries, approximate magnetic field values that deviate from reality are usually provided by the image method with the inaccurate calculation. To overcome these limitations, an analytical expression of the absorption current is derived to accurately characterize the coupling effect, thereby maintaining the high uniformity performance effectively. A forward analytical model is proposed to characterize magnetic fields, and the equivalent current could be analytically determined, which are put into the target field method (TFM) to express the superimposed the magnetic field. The inhomogeneity errors of BCs using the forward analytical model are 0.39 times of the image method. After the magnetic compensation, the signal-to-noise ratio at 0.1 Hz, 1 Hz and 10 Hz were improved by 39.5 dB, 34.3 dB, and 6.7 dB, respectively, verifying the magnetic noise can be well compensated in the whole target region. Note to Practitioners —The challenge of ensuring high signal quality in MINI-MSC for OPMs is critical in biomedical imaging applications. An forward analytical method is introduced to character the absorbed magnetic field of shielding layers, and an advanced UAMCS utilizing BCs is used for the precise magnetic field compensation to significantly enhance the signal-to-noise ratio. This approach addresses the limitations of traditional image methods, offering improved accuracy in magnetic compensation and enhance the reliability of MEG and MCG tests.

In the electrophysiological study of ischemic chronic heart failure (I-CHF) patients, cardiac electrical activity is captured using body surface electrodes in traditional electrocardiography (ECG). However, due to its limited spatial resolution, surface potential changes are reflected by ECG, and deep cardiac electrophysiological signals are struggled to be accurately detected, especially under complex pathological conditions. To address this limitation, a forward problem analytical model based on a three-dimensional cardiac-torso model for magnetocardiography (MCG) is proposed. An individualized ventricular-torso dual-domain model is constructed, and an improved diffusion equation is employed to accurately simulate the potential distribution between the endocardium and epicardium in I-CHF patients. The dynamic characteristics of the three-dimensional equivalent current density within cardiac tissue are analyzed. The simulated three-dimensional potential distribution is converted into a body surface magnetic field distribution and compared with MCGs obtained using a spin-exchange relaxation-free (SERF) magnetometer array. The proposed electromagnetic conversion analytical model demonstrates improvements in accuracy. At the peak moments of the R-wave and T-wave, significant differences in SSIM values are observed between normal individuals and ICHF patients. SSIM values for normal individuals are higher (R-wave 0.9066, T-wave 0.8537) compared to I-CHF patients (R-wave 0.8135, T-wave 0.8231). The simulated and measured data for the healthy group are consistent, while for the I-CHF group, the simulated gain and offset increase from 0.98 and 1.98 to 1.06 and 2.25, and the measured gain and offset decrease from 0.81 and 3.02 to 0.78 and 2.87. These results highlight the model’s ability to differentiate between normal and I-CHF conditions, providing a promising tool for early diagnosis of diseases.

Magnetocardiogram (MCG) requires near-zero magnetic environment, which cannot be achieved by passive shielding structure, and needs to be combined with active compensation to reduce environmental magnetic field interference. However, the environmental magnetic field is multi-directional. In this study, a multiplex coil compensation system with a matrix-based expansion magnetic field model was constructed for near-zero magnetic field environments in MCG. First, a matrix-based expansion model was established to quantify magnetic field distribution that could be used as compensation. Second, by using the particle swarm optimization algorithm with adjustable weights, the best adjustive excitation vector of the proposed matrix was obtained, despite ill-posed problems, allowing the active compensation system to suppress residual magnetic fields. Simultaneously, the multiplex compensation system was employed to follow and reduce magnetic field fluctuations in the measurement signals. Finally, cardiac magnetic signals were measured and evaluated based on the effectiveness of creating a near-zero magnetic field environment and the improvement of the signal-to-noise ratio.