Signal Space Separation Method for a Biomagnetic Sensor Array Arranged on a Flat Plane for Magnetocardiographic Applications: A Computer Simulation Study.

Kensuke Sekihara

doi:10.1155/2018/7689589

Abstract

Although the signal space separation (SSS) method can successfully suppress interference/artifacts overlapped onto magnetoencephalography (MEG) signals, the method is considered inapplicable to data from nonhelmet-type sensor arrays, such as the flat sensor arrays typically used in magnetocardiographic (MCG) applications. This paper shows that the SSS method is still effective for data measured from a (nonhelmet-type) array of sensors arranged on a flat plane. By using computer simulations, it is shown that the optimum location of the origin can be determined by assessing the dependence of signal and noise gains of the SSS extractor on the origin location. The optimum values of the parameters LC and LD, which, respectively, indicate the truncation values of the multipole-order ℓ of the internal and external subspaces, are also determined by evaluating dependences of the signal, noise, and interference gains (i.e., the shield factor) on these parameters. The shield factor exceeds 104 for interferences originating from fairly distant sources. However, the shield factor drops to approximately 100 when calibration errors of 0.1% exist and to 30 when calibration errors of 1% exist. The shielding capability can be significantly improved using vector sensors, which measure the x, y, and z components of the magnetic field. With 1% calibration errors, a vector sensor array still maintains a shield factor of approximately 500. It is found that the SSS application to data from flat sensor arrays causes a distortion in the signal magnetic field, but it is shown that the distortion can be corrected by using an SSS-modified sensor lead field in the voxel space analysis.

Highlights

Development of a sensor system that can measure biomagnetic signals in room-temperature environments has gained great interest
This paper focuses on a method called signal space separation (SSS), which was originally proposed for environmental noise cancellation for magnetoencephalography (MEG) SQUID sensor arrays [8,9,10]
This paper presents a computer simulation-based investigation that explores the possibility of applying the SSS method to data measured from an array of sensors arranged on a flat plane

Summary

Introduction

Development of a sensor system that can measure biomagnetic signals in room-temperature environments has gained great interest. A potential near-future application of such systems is a low-cost magnetocardiography (MCG) system using MR sensors [5]. Such low-cost and maintenance-free MCG systems could replace the 12-lead electrocardiogram (ECG) routinely used in daily clinical examinations. To develop such low-cost systems, one major problem is the removal of ambient noise magnetic fields that exist in urban hospital environments. To reduce the influence of such environmental noise, biomagnetic measurements have traditionally relied on two kinds of hardware-based solutions: one is magnetically shielded rooms (MSRs) and the other is gradiometer sensors [6]

Methods

Results

Conclusion