Magnetocardiogram Signals Research Articles

A new wearable multichannel magnetocardiogram system with a SERF atomic magnetometer array

In this study, a wearable multichannel human magnetocardiogram (MCG) system based on a spin exchange relaxation-free regime (SERF) magnetometer array is developed. The MCG system consists of a magnetically shielded device, a wearable SERF magnetometer array, and a computer for data acquisition and processing. Multichannel MCG signals from a healthy human are successfully recorded simultaneously. Independent component analysis (ICA) and empirical mode decomposition (EMD) are used to denoise MCG data. MCG imaging is realized to visualize the magnetic and current distribution around the heart. The validity of the MCG signals detected by the system is verified by electrocardiogram (ECG) signals obtained at the same position, and similar features and intervals of cardiac signal waveform appear on both MCG and ECG. Experiments show that our wearable MCG system is reliable for detecting MCG signals and can provide cardiac electromagnetic activity imaging.

The latest trend in magnetocardiogram measurement system technology

Heart consists of myocardium cells and the electrophysiological activity of the cells generate magnetic fields. By measuring this magnetic field, magnetocardiogram (MCG), functional diagnosis of the heart diseases is possible. Since the strength of the MCG signals is weak, typically in the range of 1-10 pT, we need sensitive magnetic sensors. Conventionally, superconducting quantum interference devices (SQUID)s were used for the detection of MCG signals due to its superior sensitivity to other magnetic sensors. However, drawback of the SQUID is the need for regular refill of a cryogenic liquid, typically liquid helium for cooling lowtemperature SQUIDs. Efforts to eliminate the need for the refill in the SQUID system have been done by using cryocooler-based conduction cooling or use of non-cryogenic sensors, or room-temperature sensors. Each sensor has advantage and disadvantage, in terms of magnetic field sensitivity and complexity of the system, and we review the recent trend of MCG technology.

Highly Sensitive Magnetic Field Sensing Using Magnetization Dynamics in Yttrium Iron Garnet Single-Crystal Thin Films

We have studied the phase change of magnetization dynamics in Bi-doped yttrium iron garnet (YIG) single-crystal thin films for a possible application of magnetic sensing. By introducing the dual-mixer time-difference method and the appropriate design of waveguide, the obtained maximum phase change was 50°/Oe. This would be acceptable for the resolution for a small magnetic field detection, such as magnetocardiogram signals. Thus, this technique using YIG is a promise candidate for the highly sensitive magnetic field sensing.

Current source reconstructing and magnetic imaging of cardiac electrical activity during P-wave

<sec> The current source reconstruction and magnetic imaging is a new technique to non-invasively obtain spatial information regarding cardiac electrical activity using magnetocardiogram (MCG) signals measured by the superconducting quantum interference device (SQUID) on the human thorax surface. Using MCG signals to reconstruct distributed current sources needs to solve the inverse problem of magnetic field. The beamforming is a type of spatial filter method that has been used for distributed source reconstruction and source imaging in electroencephalogram (EEG) and magnetoencephalogram (MEG). In this paper, the dipole moment of distributed current source is estimated with corresponding each spatial filter based on the cardiac source field model. The purpose is to enhance the intensity contrast of the dipole moment of distributed current sources in distributed source spatial spectrum estimation with beamforming, so that the reconstructed-pseudo sources beyond the heart can be removed for imaging cardiac electric activity well.</sec><sec> A new beamforming method of improving intensity contrast (IIC) of distributed source spatial spectrum estimation is developed for imaging cardiac electric activity in P-wave, due to cardiac magnetic signals in P-wave lower than that of the peak value of R-wave, which has a relatively low signal-to-noise ratio (SNR). For enhancing the accuracy of current source reconstruction in P-wave, the IIC divided into two steps: firstly, to introduce the lead-field matrix, which represents the measurement sensor-array sensitivity to magnetic field current sources, into a weight matrix of the spatial filter for making the output estimation of the filter more sensitive to the current sourcedistribution, so as to improve the intensity contrast of the reconstructed distributed sources.Secondly, by setting a threshold of source intensity from experience, to extract the reconstructed source with locally-maximal dipole strength at each time for eliminating the relatively weak pseudo sources in other locations, so as to enhance the accuracy of current source reconstruction during P-wave. In this paper, the IIC and three other methods, including minimum variance beamforming (MVB), suppressing spatial filter output noise-power gain (SONG) and trust region reflective (TRR), are compared by using the theoretical analysis and simulation experiments of MCG current source reconstruction during P-wave. The results show that the IIC has higher intensity contrast of the single source spatial spectrum estimation, and possesses better accuracy of the current source reconstruction. The 61-channel MCG signals of two healthy subjects and their imaging of cardiac electrical activity during P-wave also are analyzed. The result shows that the IIC is better than the other three methods. It is indicated that two healthy subjects have stronger electrical activity in the atrium than that in the ventricle at Ppeak time, also that the electrical activity has the direction feature when the right-atrium is depolarized during P-wave. </sec><sec> In summary, the IIC is useful for imaging the cardiac electrical activity. However, it is needed to carry out a further research on patients with local myocardial ischemia and left or right coronary artery stenosis, and to establish the evaluation index for imaging of cardiac electrical activity in such patients.</sec>

Quantitative Independent Component Selection Using Attractor Analysis for Noise Reduction in Magnetocardiogram Signals

We studied a method for reduction of environmental magnetic noise in magnetocardiograms using independent component analysis, which is a useful technique to separate signal from noise. However, this separation usually relies on subjective choices of the independent components to reconstruct the signal. Hence, we propose a method for quantitative component selection using attractor analysis and coefficient of multiple determination. We verified the noise reduction accuracy using low signal-to-noise ratio experimental data (0 and −10 dB). First, a threshold derived from the coefficient of multiple determination was determined from the results for independent component selection. Then, noise reduction accuracy was evaluated from the spatial correlation coefficients obtained using the proposed method. The results show a considerable reduction of noise for a threshold of 0.6, with its accuracy being almost equal to the maximum noise reduction accuracy obtained from the best selection pattern.

A Real-Time, Automatic MCG Signal Quality Evaluation Method Using the Magnetocardiography and Electrocardiography

The quality of the obtained Magnetocardiogram (MCG) signal has significant influence on the reliability of deriving some important parameters, such as the interval between two R waves (RR interval), the interval between Q wave and the adjacent T wave (QT interval) and the interval between S wave and the adjacent T wave (ST interval), etc. The poor MCG signal might falsely trigger alarms frequently. The induced overloading of alarms can lead to alarm fatigue, and eventually reduce the care staffs’ attention level. Therefore, a real-time MCG signal quality evaluation algorithm is of great importance. It can allow inexperienced care staffs to collect MCG signals with sufficiently good diagnostic quality. In this work, we proposed an automatic MCG signal quality evaluation algorithm based on the multiparameters derived from MCG data and electrocardiogram (ECG) data. These MCG and ECG data are collected simultaneously. Unlike the available methods for evaluating the signal quality, seven parameters were extracted from the MCG and ECG data. For evaluation purpose, each parameter goes into two categories (good or poor) according to the set threshold. The quality of the MCG signal is evaluated according to the majority rule. The performances of the proposed algorithm were tested in a nine-channel MCG system. The achieved accuracy was 91%. Having demonstrated lower complexity and high accuracy, the proposed algorithm is promising for the real-time MCG signal quality evaluation.

Suppression of Baseline Wander Artifact in Magnetocardiogram Using Breathing Sensor

Measurements of magnetocardiogram (MCG) are commonly contaminated by different types of artifacts like breathing, power line interference and subject’s movement, out of which artifact due to breathing is unavoidable. This breathing artifact is mainly caused by movement of the chest of the subject during respiration and the consequent changes of the distance between the superconducting quantum interference device (SQUID) sensors (used for recording the MCG signal) and the subject (lying in a supine position under the cryostat housing the SQUID sensors); because of this, the measured MCG signal is a superposition of the true MCG signal of cardiac origin and the breathing related artifact. In most previous works, the suppression of baseline wander artifact was implemented by using digital filters, wavelet based technique, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD). We present here a novel approach for effective suppression of breathing related baseline wander artifacts by acquiring the MCG data contaminated by the breathing artifact simultaneously with the experimental recording of the actual breathing pattern of the subject using a temperature sensor. The temperature sensor monitors the very slight change in temperature that occurs near the nostril during inhalation and exhalation, and this data is used for the subsequent elimination of the breathing artifact from the contaminated MCG by using the regression approach. We illustrate the method and compare its performance with other conventional approaches for the suppression of baseline wander in the measurement of MCG using single channel data. This is the first time that a breathing sensor has been employed for the suppression of breathing related baseline wander artifact. Experimental results reveal the superiority of the proposed approach in suppression of the breathing related base-line wander artifact with the important advantage that the algorithm used for the suppression uses the actual breathing data derived from an experimental input.

Comparison of Electric- and Magnetic-Cardiograms Produced by Myocardial Ischemia in Models of the Human Ventricle and Torso

Myocardial ventricular ischemia arises from a lack of blood supply to the heart, which may cause abnormal repolarization and excitation wave conduction patterns in the tissue, leading to cardiac arrhythmias and even sudden death. Current diagnosis of cardiac ischemia by the 12-lead electrocardiogram (ECG) has limitations as they are insensitive in many cases and may show unnoticeable differences to normal patterns. As the magnetic field provides extra information on cardiac excitation and is more sensitive to tangential currents to the surface of the chest, whereas the electric field is more sensitive to flux currents, it has been hypothesized that the magnetocardiogram (MCG) may provide a complementary method to the ECG in ischemic diagnosis. However, it is unclear yet about the differences in sensitivity regions of body surface ECG and MCG signals to ischemic conditions. The aim of this study was to investigate such differences by using 12-, 36- ECG and 36-MCG computed from multi-scale biophysically detailed computational models of the human ventricles and torso in both control and ischemic conditions. It was shown that ischemia produced changes in the ECG and MCG signals in the QRS complex, T-wave and ST-segment, with greater relative differences seen in the 36-lead ECG and MCG as compared to the 12-leads ECG (34% and 37% vs 26%, respectively). The 36-lead ECG showed more averaged sensitivity than the MCG in the change of T-wave due to ischemia (37% vs 32%, respectively), whereas the MCG showed greater sensitivity than the ECG in the change of the ST-segment (50% vs 40%, respectively). In addition, both MCG and ECG showed regional-dependent changes to ischemia, but with MCG showing a stronger correlation between ischemic region in the heart. In conclusion, MCG shows more sensitivity than ECG in response to ischemia, which may provide an alternative method for the diagnosis of ischemia.

Closed-cycle cryocooled SQUID system with superconductive shield for biomagnetism

We developed a cryocooled SQUID system with which human magnetocardiogram (MCG) and possibly magnetoenceparogram (MEG) can be measured. To reduce cyclic magnetic noises originating from the regenerator of the cold heads of the cryocooler, a superconductive shield (99.5% Pb) was used to protect the SQUID sensors, and a ferromagnetic shield (78% Ni alloy) was used to screen the cold head. In addition, the SQUID sensors’ chamber was placed at a distance of 1.8 m from the cold head chamber to install the cold-head chamber outside the magnetically shielded room (MSR) for future development. The loss in cooling power due to the increased distance was compensated by increasing the number of thermal rods, and thus the SQUID sensor and superconductive shield could be refrigerated to 4.8 K and 5 K, respectively. The superconductive shield successfully rejected thermal noise emitted from metallic blocks used to improve thermal conduction. The noise of the SQUID system was 3 fT/Hz1/2, and the cyclic magnetic noise could be reduced to 1.7 pT. We could obtain a clear MCG signal while the entire cryogenics was in operation without any special digital processing.

Distributed current source reconstruction of magnetocadiography and its accuracy analysis

Reconstructing cardiac current source by magnetocardiogram signal is a noninvasive method of revealing cardiac electrical activity. The visualization of spatial and temporal information about cardiac electrical activity will be conducive to the analysis of the heart function and the diagnosis of heart disease. In this paper, the capability of reconstructing distribution of current sources, whose distribution is changed over time, is studied by a reduced time window (RTW) beamformer, and the relationship between source reconstruction results and ventricular excitation propagation is analyzed in simulation. The cellular automaton is used to simulate ventricular excitation propagation and to generate the current sources. Moreover, a heart-torso model is constructed by the boundary element method to simulate the effect of the volume conductor. The simulation results show that the RTW beamformer can provide a good accuracy of reconstructing the distribution of current sources. The RTW beamformer is also used to analyze a normal subject with the lead field of infinite homogeneous medium. The results demonstrate that they reflect the basic characteristic of ventricular excitation propagation.

A Measurement of Magnetocardiogram (MCG) in Multi Point using a Transmission Line Type Thin-Film Sensor

We have developed a very sensitive thin film sensor using a transmission line. The sensor element consists of a coplanar line fabricated from a ceramic substrate and amorphous-CoNbZr film (4μm in thickness). The ceramic substrate with high permittivity enhances the phase change of the carrier, phase change around 7000 degree/Oe being achieved. A small phase change was detected using a Dual Mixer Time Difference (DMTD) method when a weak magnetic field are applied. We applied the sensor for magnetocardiogram (MCG) measurement using the phase detection technique. We succeeded in measuring the MCG signals in multi point, including a typical QRS wave and T wave, and this signals were found to roughly agree with already reported MCG data by SQUID.

Parameter decision of independent component analysis for low SNR magnetocardiogram signal

Event Abstract Back to Event Parameter decision of independent component analysis for low SNR magnetocardiogram signal Koichiro Kobayashi1*, Masahito Yoshizawa1 and Yoshinori Uchikawa2 1 Iwate University, Japan 2 Tokyo Denki University, Japan Recently, clinical applications of magnetocardiograms (MCGs) have been widely studied. It is useful diagnosis such as the conduction process and evaluation of ischemic heart disease. However, it is difficult to make a correct diagnosis that MCGs are very low signal to noise ratio (SNR), for example MCGs measured outside a magnetically shielded room. Many noise reduction methods are proposed for biomagnetic measurements, especially independent component analysis (ICA) is a useful method for separating the signal and the noise. But ICA has some problems that are to decide many parameters and to distinguish signal or noise components from separated components. In many case, these were decided by experiential results. It was difficult to decide optimum parameters. We proposed the method of independent components that separated by the ICA and the decision method of the number of the contraction dimension. As a method of independent components, the components which synchronized with the autocorrelation of electrocardiogram and that of independent components are chosen as the signal components. As a dimension contraction method, the dimension of which the highest autocorrelation in the each contraction dimension is chosen. In order to evaluate the proposed method, the simulation study was carried out for various SNR MCGs. For the comparison, the method using linear discriminant analysis was carried out. In the component of MCG (SNR= -10dB), the correlation coefficient of the proposed method becomes 0.9 which is 0.2 higher than that of linear discriminant analysis. In the dimension contraction, the proposed method agreed almost with largest correlation coefficient calculated from all contraction dimensions. It was shown that proposed method was effective for the decision method of independent components and the number of the contraction dimension. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: MCG: Instrumentation, Modeling, Basic and Clinical Studies Citation: Kobayashi K, Yoshizawa M and Uchikawa Y (2010). Parameter decision of independent component analysis for low SNR magnetocardiogram signal. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00314 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 06 Apr 2010; Published Online: 06 Apr 2010. * Correspondence: Koichiro Kobayashi, Iwate University, Iwate, Japan, kobaya@iwate-u.ac.jp Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Koichiro Kobayashi Masahito Yoshizawa Yoshinori Uchikawa Google Koichiro Kobayashi Masahito Yoshizawa Yoshinori Uchikawa Google Scholar Koichiro Kobayashi Masahito Yoshizawa Yoshinori Uchikawa PubMed Koichiro Kobayashi Masahito Yoshizawa Yoshinori Uchikawa Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

A thin film magnetic field sensor of sub-pT resolution and magnetocardiogram (MCG) measurement at room temperature

We developed a very sensitive high-frequency carrier-type thin film sensor with a sub-pT resolution using a transmission line. The sensor element consists of Cu conductor with a meander pattern (20 mm in length, 0.8 mm in width, and 18 μm in thickness), a ground plane, and amorphous CoNbZr film (4 μm in thickness). The amplitude modulation technique was employed to enhance the magnetic field resolution for measurement of the high-frequency field (499 kHz), a resolution of 7.10×10 −13 T/Hz 1/2 being achieved, when we applied an AC magnetic field at 499 kHz. The phase detection technique was applied for measurement of the low frequency field (around 1 Hz). A small phase change was detected using a dual mixer time difference method. A high phase change of 130°/Oe was observed. A magnetic field resolution of 1.35×10 −12 T/Hz 1/2 was obtained when a small AC field at 1 Hz was applied. We applied the sensor for magnetocardiogram (MCG) measurement using the phase detection technique. We succeeded in measuring the MCG signal including typical QRS and T waves, and compared the MCG with a simultaneously obtained conventional electrocardiogram (ECG) signal.

A Novel Filter Scheme of Data Processing for SQUID-Based Magnetocardiogram

We present a new filter scheme for magnetocardiogram (MCG) signal processing based on the quasi-periodic characteristic of the signals. The key points of this scheme are to determine the exact numbers of data points in each cardiac cycle by using electrocardiogram (ECG) data acquired simultaneously with the MCG signal and to normalize the MCG data sequence in each cycle into an identical length. Compared with conventional filters, the scheme has the advantage of more powerful noise suppression with less signal distortion. The desire for having high quality output signals from raw MCG data acquired in a simple shielded room or even in unshielded environment may be realized with the scheme.

64-channel second-order axial gradiometer system based on DROS for magnetocardiogram in a thin shielded room

We fabricated a magnetocardiogram (MCG) system having 64 second-order wire-wound gradiometers for operation inside a thin magnetically shielded room (MSR). In order to provide good quality MCG signals in noisy environments using a thin economic shielded room, we used second-order gradiometers with a baseline of 70 mm. In order to reduce the liquid level necessary to cool the sensor into superconducting state, the total length of the gradiometer was reduced to 160 mm by using a special superconducting connection method between pickup coil and input coil. The SQUID sensor is the low-temperature double relaxation oscillation SQUID (DROS) having large flux-to-voltage transfers to simplify the readout electronics. The coverage area of the 64-channel sensor array is about 256 mm. The MSR is consisted of 1 layer of 1.4-mm thick Permalloy and 1 layer of 12-mm thick Al. The thin MSR has shielding factors of about 17 at 0.1 Hz and 300 at 10 Hz. When the second-order gradiometer system was operated inside the thin MSR, the average noise level is about 7 fT/√Hz at 200 Hz.

As-grown MgB2 薄膜を用いた DC-SQUID の作製

We have developed DC-SQUID using an as-grown MgB2 film for devices detecting magnetocardiogram (MCG) and other purposes. Our as-grown MgB2 film was fabricated by a low-temperature co-evaporation method on a c-plane sapphire substrate using a molecular beam epitaxy (MBE) apparatus. A nano-bridge DC-SQUID was fabricated using a standard lithography technique with a focused ion beam (FIB) apparatus. The modulation voltage is in the range of 10 μV and 100 μV, dependent on temperature. We have successfully detected the MCG signals.

Whole heart modeling: from validation of animal experiments to the reconstruction of the human magnetocardiogram

Our interest in heart modeling is on one hand strongly motivated by the desire to compare cardiac simulation results with data obtained from magnetocardiogram (MCG) measurements of human beings and animals in various setups. On the other hand, we have started to integrate imaging data at various levels in our modeling approach. In the first part, we report in detail on simulations of anatomically realistic models for animal ventricles using the modified Beeler-Reuter ionic model and compare these with experimental data. Simulations of a rabbit heart were carried out and compared with experiments in Langendorff perfusion. The time evolution of the spatial profiles of the extracellular potential on the surface of the rabbit heart was correctly reproduced. The effects of ajmaline (Na-channel blockage) and palmitoleic acid (decrease of intracellular conductivity) were included subsequently in the model. In addition, pacing simulations of the ventricles have been performed using different frequencies. Occurrence of action potential duration alternans was found for frequencies greater than 230 bpm. Fibrillation occurred for frequencies greater than 260 bpm. Finally, the influence of geometry change during the human heart beat on MCG signals was investigated. We computed the MCG using the ten Tusscher ionic model for 2-dimensional cuts through the ventricles recorded by magnetic resonance imaging during systole resp. diastole and found a much shorter QRS for the diastolic geometry. Furthermore, the dynamic geometry of the heart was recorded and translated into a moving finite element mesh used in 3-dimensional simulations of the heart.

Fetal source extraction from magnetocardiographic recordings by dependent component analysis

Fetal magnetocardiography (fMCG) has been extensively reported in the literature as a non-invasive, prenatal technique that can be used to monitor various functions of the fetal heart. However, fMCG signals often have low signal-to-noise ratio (SNR) and are contaminated by strong interference from the mother's magnetocardiogram signal. A promising, efficient tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). Herein we propose an algorithm based on a variation of ICA, where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We model the system using autoregression, and identify the signal component of interest from the poles of the autocorrelation function. We show that the method is effective in removing the maternal signal, and is computationally efficient. We also compare our results to more established ICA methods, such as FastICA.

Development of Mice Biomagnetic Measurement System Using dc-SQUID Magnetometer

A biomagnetic measurement system on mice using a dc superconducting quantum interference device magnetometer has been developed. We are going to use it for comparative magnetoencephalogram (MEG) and magnetocardiogram (MCG) studies of transgenic mice to clarify the functional influence of gene modification in a living body. The system has a low-T/sub c/ direct coupled dc SQUID. A focuser type pickup coil whose outside/inside diameter is 1 mm/100 /spl mu/m was adopted for detailed functional mapping of the brain or the heart of mice. The minimum lift-off distance was reduced to 700 /spl mu/m to achieve the sufficient spatial resolution and magnetic field sensitivity. The field sensitivity of this system is 1.3 pT/Hz/sup 1/2/ in the white-noise region (10 Hz-10 kHz). The MCG of a wild mouse at 9-months of age was measured and compared with the data of 3-month old mice. The spatial and time changes of MCG signals were similar in both ages of mice, while the amplitude of MCG signals of 9-month mice was less than 40% of that of 3-month mice. This decrease in MCG amplitude may be due to aging. The result suggested the capability of our system in evaluating the mice MCG signals.

心疾患モデルマウスの非侵襲心機能マッピング―マウス心磁図計測のための高空間分解能ＳＱＵＩＤシステムの開発―

Recently, a large variety of disease-model experimental animals, which are generated by gene modification or drug inducement, have become available for studying disease development and treatment. Biomagnetic measurement has been considered a powerful tool in the study of disease-model animals since it is a completely non-invasive and contact-free technique for the functional mapping of a living body. This paper reviews the biomagnetic studies of experimental animals for the purpose of elucidating the electrophysiological functions of the brain and heart, and introduces our newly developed magnetocardiogram (MCG) measurement system for mice. We have developed the system using a dc superconducting quantum interference device (SQUID) magnetometer to make comparative MCG studies of disease-model mice in order to clarify the mechanism of disease development in a living body. We measured the MCG of wild-type (control) and aconitine-induced arrhythmia model mice. The difference in the spatial distribution and time course of the MCG signals between regular sinus rhythm and arrhythmia was clearly evaluated. The results suggest that the system presented is capable of screening the cardiac excitation pathway of mice in good spatial and time resolution.