Measuring the Electromagnetic Field of Human Subjects Using Induction Sensors and a Shielded Helmet Without the Need for a Shielded Room.

Cureus · 2022 · Unclear · Very low evidence

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UnclearVery low evidencePaper 5741

Across trials, FFT data differed between background (no subject) and subject rest/activity conditions, and differences were observed between rest and activity phases within individuals. The authors conclude that shielding via a Mu-metal/copper mesh helmet and…

Study snapshot

PublicationCureus · 2022
Study typeengineering
Reported directionUnclear
Evidence ratingVery low

Abstract

Introduction Neurologic activity is mediated by electrochemical signaling pathways that generate an electric charge. These electrical signals generate electromagnetic fields (EMF) that have been found to be measurable through magnetoencephalography and induction sensors. These technologies typically rely on expensive shielding via shielded rooms to remove influence from the external environment. We aimed to investigate the effects of a lightweight shielded helmet constructed of Mu-metal and interlaced copper mesh and Mu-metal EMF "channels" on shielding externally mediated EMF when measuring cortically generated EMF during human activity. Methods Non-contact, non-invasive, proprietary induction sensors were utilized with a combination of a dual-layer Mu-metal and interlaced copper mesh helmet with sensors placed within EMF channels connected to the helmet. Five human volunteers participated in motor activities, verbalization activities, and visual object naming to evaluate the effectiveness of shielding solely via the helmet and EMF channel construct on generated EMF without placement of individuals within a shielded room. Background data without a subject were obtained. Results Differences in fast Fourier transformed data were noted in the background compared to rest and various activities throughout all trials. There were differences in rest phases and activity phases in each individual identifying active measurement of differences in cortically generated EMF during each activity. Conclusion It appears that eliminating a Mu-metal shielded room is possible when shielding is isolated to the helmet and EMF channels with induction sensors. The external EMF was appropriately excluded with differences in background data in all trials. During the activity, differences were noted between rest phases and activity phases in all activities noting the discernibility of these induction sensors in measuring cortically generated EMF. Measured activity through motor tapping with changes between 4 and 6 Hz appeared to correlate with previously documented changes during motor activity using these sensors in conjunction with shielded rooms.

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeengineering
Effect directionunclear
PopulationHuman volunteers
Sample size5
ExposureNot supplied
Evidence strengthVery lowConfidence: 74% · Peer reviewed: yes

Main findings

Across trials, FFT data differed between background (no subject) and subject rest/activity conditions, and differences were observed between rest and activity phases within individuals. The authors conclude that shielding via a Mu-metal/copper mesh helmet and EMF channels may allow measurement of cortically generated EMF with induction sensors without using a shielded room, with motor tapping showing changes between 4 and 6 Hz that appeared to correlate with prior shielded-room measurements.

Outcomes measured

  • Ability of a Mu-metal/copper mesh shielded helmet with EMF channels to exclude external EMF during induction-sensor measurements
  • Differences in FFT data between background, rest, and activity phases during motor, verbalization, and visual object naming tasks
  • Observed frequency changes (4–6 Hz) during motor tapping

Limitations

  • Very small sample size (five volunteers)
  • Use of proprietary induction sensors (details not provided in abstract)
  • No quantitative performance metrics for shielding effectiveness reported in abstract
  • No explicit control condition using a shielded room described in abstract
View raw extracted JSON
{
  "study_type": "engineering",
  "exposure": {
    "band": null,
    "source": null,
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": null
  },
  "population": "Human volunteers",
  "sample_size": 5,
  "outcomes": [
    "Ability of a Mu-metal/copper mesh shielded helmet with EMF channels to exclude external EMF during induction-sensor measurements",
    "Differences in FFT data between background, rest, and activity phases during motor, verbalization, and visual object naming tasks",
    "Observed frequency changes (4–6 Hz) during motor tapping"
  ],
  "main_findings": "Across trials, FFT data differed between background (no subject) and subject rest/activity conditions, and differences were observed between rest and activity phases within individuals. The authors conclude that shielding via a Mu-metal/copper mesh helmet and EMF channels may allow measurement of cortically generated EMF with induction sensors without using a shielded room, with motor tapping showing changes between 4 and 6 Hz that appeared to correlate with prior shielded-room measurements.",
  "effect_direction": "unclear",
  "limitations": [
    "Very small sample size (five volunteers)",
    "Use of proprietary induction sensors (details not provided in abstract)",
    "No quantitative performance metrics for shielding effectiveness reported in abstract",
    "No explicit control condition using a shielded room described in abstract"
  ],
  "evidence_strength": "very_low",
  "confidence": 0.74,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "electromagnetic field",
    "EMF",
    "magnetoencephalography",
    "induction sensors",
    "Mu-metal",
    "copper mesh",
    "shielding",
    "helmet",
    "FFT",
    "motor activity",
    "verbalization",
    "visual object naming"
  ],
  "suggested_hubs": []
}
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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.7759/cureus.24107
PubMed: 35573536

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