research Paper: Atomic Gradiometer for Recording the Simulated Human Brain Signal in Unshielded Environment

Document Type : Research Paper

Authors

1 Professor, Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran

2 M.Sc. Student, Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran

3 Assistant Professor, Department of Physics, Central Tehran Branch, Islamic Azad University, Tehran, Iran

4 Assistant Professor, Department of Physics, Kharazmi University, Tehran, Iran

Abstract

The fields resulting from the brain's neural activities provide essential information in diagnosing and treating brain diseases such as epilepsy, convulsions, and brain tumors. Recording brain magnetic field signals is one of the non-invasive brain functional imaging methods, which usually requires magnetic shielding besides expensive and bulky instruments. Although atomic magnetometers are inherently less sensitive than superconducting quantum interference devices, they are considered the best candidate for measuring bio-magnetic fields due to their low manufacturing cost, small size, and no need for cryogenic equipment. Atomic magnetometers measure the low-strength brain magnetic fields based on detecting Zeeman energy splitting and recording changes in the laser light intensity passing through an alkali vapor cell. To improve the sensitivity of these magnetometers, it is common to remove homogeneous noises in two magnetometer channels. For this purpose, we have presented a gradiometer to suppress unwanted magnetic noises. This gradiometer consists of two atomic magnetometers capable of detecting the field produced by the human brain in an unshielded environment in the presence of the Earth's magnetic field. The gradiometer has a sensitivity of 900 fT⁄√Hz. The designed and built gradiometer is suitable for detecting brain magnetic fields, which can be expanded as a multichannel to record the map of the brain's magnetic field.

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References

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History

  • Receive Date: 13 August 2023
  • Revise Date: 28 November 2023
  • Accept Date: 19 January 2024

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