The relationship between anatomically correct electric and magnetic field dosimetry and publishedelectric and magnetic field exposure limits

Kavet, Robert; Dovan, T.; Reilly, J.P.

doi:10.1093/rpd/ncs064

Cited by 12 publications

(6 citation statements)

References 29 publications

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“…It is essential to assign an appropriate conductivity distribution to the volume conductor model [ 36 ]. Although extremely low skin conductivities have been reported in specific studies, in the present study, the conductivity of the skin is assigned as 0.1 S/m [ 35 ]. Lower values could correspond to the stratum corneum [ 37 ] and are thus inappropriate to be used here.…”

Section: Methodsmentioning

confidence: 84%

“…In TARO, the heart is represented by only one tissue; the atrium and ventricle are not explicitly identified. The electrical conductivity of the TARO model ( Table 1 ) is computed based on the 4-Cole–Cole model at 1 Hz; the conductivity of the skin is assigned a value of 0.1 S/m [ 34 , 35 ]. Moreover, a homogeneous whole-body model created by changing the structure of TARO into a single homogenous tissue is also considered for comparison.…”

Section: Methodsmentioning

confidence: 99%

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ECG Localization Method Based on Volume Conductor Model and Kalman Filtering

Nakano

Rashed

Nakane

et al. 2021

Sensors

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The 12-lead electrocardiogram was invented more than 100 years ago and is still used as an essential tool in the early detection of heart disease. By estimating the time-varying source of the electrical activity from the potential changes, several types of heart disease can be noninvasively identified. However, most previous studies are based on signal processing, and thus an approach that includes physics modeling would be helpful for source localization problems. This study proposes a localization method for cardiac sources by combining an electrical analysis with a volume conductor model of the human body as a forward problem and a sparse reconstruction method as an inverse problem. Our formulation estimates not only the current source location but also the current direction. For a 12-lead electrocardiogram system, a sensitivity analysis of the localization to cardiac volume, tilted angle, and model inhomogeneity was evaluated. Finally, the estimated source location is corrected by Kalman filter, considering the estimated electrocardiogram source as time-sequence data. For a high signal-to-noise ratio (greater than 20 dB), the dominant error sources were the model inhomogeneity, which is mainly attributable to the high conductivity of the blood in the heart. The average localization error of the electric dipole sources in the heart was 12.6 mm, which is comparable to that in previous studies, where a less detailed anatomical structure was considered. A time-series source localization with Kalman filtering indicated that source mislocalization could be compensated, suggesting the effectiveness of the source estimation using the current direction and location simultaneously. For the electrocardiogram R-wave, the mean distance error was reduced to less than 7.3 mm using the proposed method. Considering the physical properties of the human body with Kalman filtering enables highly accurate estimation of the cardiac electric signal source location and direction. This proposal is also applicable to electrode configuration, such as ECG sensing systems.

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Section: Methodsmentioning

confidence: 84%

Section: Methodsmentioning

confidence: 99%

ECG Localization Method Based on Volume Conductor Model and Kalman Filtering

Nakano

Rashed

Nakane

et al. 2021

Sensors

View full text Add to dashboard Cite

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“…As indicated in Results, ICNIRP permits extending into subcutaneous tissue when averaging for skin [2]. This is based on recognizing both skin and fat as surrogates for PNS, even without rigorous validation [45]. We suggest (subsection III.F) that for skin, at least ∼10% air inclusion is necessary for reproducibly averaged electric fields with different voxel resolutions, even when subcutaneous tissues are also included in the averaging (Fig.…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Spatial Averaging Schemes of In Situ Electric Field for Low-Frequency Magnetic Field Exposures

et al. 2019

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ICNIRP and IEEE publish standards/guidelines for exposures to low-frequency electromagnetic fields and their associated in situ electric fields. Two methods are prescribed for spatially averaging the in situ electric field to evaluate compliance: averaging (1) over a 2 mm × 2 mm × 2 mm volume (ICNIRP) and (2) along a 5 mm linear segment of neural tissue (IEEE). However, detailed calculation procedures for these two schemes are not provided, particularly when the averaging volume/line straddles a tissue/air or tissue/tissue interface. This study proposes detailed schemes for implementing the volume-and lineaveraging in such cases, applying them to both a spherical model of layered tissues and a human anatomical model. To extend the applicability of the proposed averaging schemes to the voxels at the tissue boundaries, a parameter, p max , is introduced and defined as the maximum permissible percentage of air/other tissues in the averaging volume/line. For most inner-tissue voxels results show good agreement between the two averaging schemes, in general. Excluding skin, the relative differences between the two averaging schemes were less than 9% for the 99 th percentile in situ electric field, and these differences decrease as p max increases. Results indicate that around 20-30% inclusion of air or other tissues for volume averaging of internal tissues provides stable percentile values; less stability is observed across p max for linear averaging. Invoking the suggestion of ICNIRP (2010) that the averaging cube for skin ''may extend to subcutaneous tissue,'' ≥10% inclusion of air results in stable averaged induced electric fields.

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“…The electrical conductivity of the tissues is assigned based on the 4-Cole-Cole model [28]. The skin's conductivity is assigned as 0.1 S/m [29] because extremely low conductivities have been reported by a few studies, which correspond to the stratum corneum [30].…”

Section: Methods and Model A Anatomical Human Body Modelmentioning

confidence: 99%

Forward Electrocardiogram Modeling by Small Dipoles Based on Whole-Body Electric Field Analysis

et al. 2019

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Mathematical modeling of detailed cardiac function has become possible in recent years. Computer simulations have been conducted to reproduce electrical phenomena of the heart. However, substantial effort and computational cost are required to construct an electrocardiogram (ECG) generation model based on multiple parameters of cardiac tissue. In addition, most previous studies simplified the anatomy and the region of the body considered. Such modeling may not be applicable for the system design of wearable sensing in ECG. In this study, we propose a computational model of ECG generation with multiple electric dipoles to reduce the complexity and computational cost of ECG modeling. In this study, first, the electrical potential distribution on the surface of an anatomically detailed model was computed with volume conductor (electrical) analysis. We subsequently simulated the propagation of the electrical excitation of the heart by sequentially placing electric dipoles according to conduction velocity. Our computational results demonstrate the effectiveness of the ECG model using electric dipoles in comparison with measurement and the necessity to discuss the ground in a 12-lead ECG for the whole-body model. The required computational time was less than 30 min even in a workstation (2 CPUs, 28 cores, and 2.20 GHz), i.e., significantly less than those of previous studies.INDEX TERMS Electrocardiography, electromagnetic modeling, finite difference methods.

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The relationship between anatomically correct electric and magnetic field dosimetry and publishedelectric and magnetic field exposure limits

Cited by 12 publications

References 29 publications

ECG Localization Method Based on Volume Conductor Model and Kalman Filtering

ECG Localization Method Based on Volume Conductor Model and Kalman Filtering

Spatial Averaging Schemes of In Situ Electric Field for Low-Frequency Magnetic Field Exposures

Forward Electrocardiogram Modeling by Small Dipoles Based on Whole-Body Electric Field Analysis

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