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Design of a stimulation protocol to predict temperature distribution in subcutaneous tissue using the finite element model.
Myoung, Hyoun-Seok; Kim, Dong-Hyun; Kim, Han-Sung; Lee, Kyoung-Joung.
Affiliation
  • Myoung HS; Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwondo 220-710 Republic of Korea.
  • Kim DH; Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwondo 220-710 Republic of Korea.
  • Kim HS; Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwondo 220-710 Republic of Korea.
  • Lee KJ; Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwondo 220-710 Republic of Korea.
Biomed Eng Lett ; 7(3): 261-266, 2017 Aug.
Article in En | MEDLINE | ID: mdl-30603174
ABSTRACT
Moxibustion is a traditional Oriental medicine therapy that treats the symptoms of a disease with thermal stimulation. However, it is difficult to control the strength of the thermal or chemical stimulus generated by the various types and amounts of moxa and to prevent energy loss through the skin. To overcome these problems, we previously developed a method to efficiently provide RF thermal stimulation to subcutaneous tissue. In this paper, we propose a finite element model (FEM) to predict temperature distributions in subcutaneous tissue after radio-frequency thermal stimulation. To evaluate the performance of the developed FEM, temperature distributions were obtained from the FEM, and in vivo experiments were conducted using the RF stimulation system at subcutaneous tissue depths of 5 and 10 mm in the femoral region of a rabbit model. High correlation coefficients between simulated and actual temperature distributions-0.98 at 5 mm and 0.99 at 10 mm-were obtained, despite some slight errors in the temperature distribution at each depth. These results demonstrate that the FEM described here can be used to determine thermal stimulation profiles produced by RF stimulation of subcutaneous tissue.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Biomed Eng Lett Year: 2017 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Biomed Eng Lett Year: 2017 Document type: Article
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