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Related Experiment Video

Updated: Aug 28, 2025

Employing Transcranial Magnetic Stimulation in a Resource Limited Environment to Establish Brain-Behavior Relationships
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Devices and Technology in Transcranial Magnetic Stimulation: A Systematic Review.

Mario Ibrahin Gutierrez1, Irais Poblete-Naredo2, Jorge Airy Mercado-Gutierrez3

  • 1Subdirección de Investigación Tecnológica, División de Investigación en Ingeniería Médica, CONACYT -Instituto Nacional de Rehabilitación LGII, Mexico City 14389, Mexico.

Brain Sciences
|September 23, 2022
PubMed
Summary
This summary is machine-generated.

This review analyzes the evolution of transcranial magnetic stimulation (TMS) technology, highlighting advancements in signal generators, coils, and positioning systems. Future development should focus on optimizing current technology and validating models for broader applications.

Keywords:
TMS coilTMS devicesTMS modelingTMS stimulatorTMS technologytranscranial magnetic stimulation

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Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Medical Technology

Background:

  • Transcranial magnetic stimulation (TMS) technology has undergone significant evolution.
  • Improvements have been made in signal generators, coils, positioning systems, and software for modeling and therapy planning.

Purpose of the Study:

  • To systematically review and analyze the technological advancements in TMS.
  • To identify limitations and areas for future development in TMS technology.

Main Methods:

  • A systematic literature review (SLR) following the PRISMA 2020 statement.
  • Searched four databases (Web of Science, PubMed, Scopus, IEEE) for TMS technology articles, excluding conference papers and reviews.
  • 101 relevant articles were included after screening for new technological developments.

Main Results:

  • The review identified 19 new stimulator designs (18.8%), 46 coil advancements (45.5%), 18 coil placement systems (17.8%), and 43 optimization algorithms (42.6%).
  • Analysis revealed a strong focus on coil technology and optimization algorithms.

Conclusions:

  • Further emphasis is needed on optimizing existing TMS technology.
  • Experimental validation of computational models is crucial for advancing TMS applications in neurological and psychiatric diseases.