Blood oxygenation changes resulting from subthreshold high frequency repetitive transcranial magnetic stimulation

Rihui Li, Chushan Wang, Kairong Huang, Zhixi Shi, Jun Wang, Yingchun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Effects of high frequency repetitive transcranial magnetic stimulation (rTMS) with a subthreshold intensity on hemodynamic response in brain cortices (both motor and prefrontal cortices) was investigated using the functional near infrared spectroscopy (fNIRS) technique. FNIRS signals of the motor and prefrontal cortices were acquired in healthy volunteers (n=7) at rest and during rTMS intervention. A significant reduction in oxygenated hemoglobin (HbO) concentration during the entire stimulation process was observed from both motor and prefrontal cortices. Results showed that the fNIRS technique can provide a reliable measure of regional cortical brain activation that could be valuable in studying cortical excitability connectivity in combination with rTMS.

Original languageEnglish (US)
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1513-1516
Number of pages4
ISBN (Electronic)9781509028092
DOIs
StatePublished - Sep 13 2017
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: Jul 11 2017Jul 15 2017

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
Country/TerritoryKorea, Republic of
CityJeju Island
Period7/11/177/15/17

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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