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A Study on the Characteristics of an EEG Based on a Singing Bowl’s Sound Frequency

  • Ik-Soo Ahn
  • Bong-Young Kim
  • Kwang-Bock You
  • Myung-Jin Bae
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 789)

Abstract

We analyzed the sound of a singing bowl, which is used as a method to restore and maintain the balance of the natural frequency of the human body, and studied the EEG (electroencephalogram) of the listener according to the frequency band of the singing bowl’s sounds. The singing bowl’s sound has a wide range of frequencies that can restore all of the natural frequencies of the human body, thus helping the body recover or heal. The low frequency band of the singing bowl’s sound was the most energy-intensive across the whole band, followed by a decrease in energy in the order of the mid-frequency band and the high-frequency band. The singing bowl is a tool designed to help people heal and recover, thus it’s sounds aim to gives stability and comfort to people’s mind and body as a whole. A study on the brain wave characteristics of listeners corresponding on the frequency bands of a singing bowl’s sounds will provide useful data for using singing bowls and it is hoped that this study will contribute to the development of other sound healing tools.

Keywords

Sound Human body Influence Singing bowl’s sound Healing Frequency EEG 

References

  1. 1.
    Ryu, J.-S.: A comparative study on the effectiveness of surface electromyography in the treatment of shoulder cuffs using magnets, tuned ankles and clans. Master’s Thesis, Kyonggi University (2008)Google Scholar
  2. 2.
    Lee, C.-S.: Eastern and Western Therapy for Sound (monthly) Practical Special Education (2015)Google Scholar
  3. 3.
    Shi-a Chun Station, Shuren Shrestha: Singing Bowl Healing. Genbook (2015)Google Scholar
  4. 4.
    Jeon, H.-S.: J. Korean Soc. Hortic. Sci. Technol. (2008)Google Scholar
  5. 5.
    Choi, H.-S.: The effect of sound therapy on training therapy. Master Thesis, Yonsei University (2007)Google Scholar
  6. 6.
    Kim, Y.-W.: Comparison of THI Changes According to the Duration of TRT, Sound Therapy Tools, and Lingual Counseling. Hallym University Graduate University (2009)Google Scholar
  7. 7.
    Lee, Y.-H.: What is Sound Therapy? Academic papers, Korea Occupational Health Association (2003)Google Scholar
  8. 8.
    Bae, M.-J., Lee, S.-H.: Digital Speech Analysis (1998)Google Scholar
  9. 9.
    Rabiner, L.R., Schafer, R.W.: Theory and Applications of Digital Speech Processing. Pearson (2010)Google Scholar
  10. 10.
    Kang, S.H., Jung, S.H., Jung, H.K., Lee, J.W. (eds.): Analysis of Reverberation time. The Acoust. Soc. Korea, 311–314 (2010)Google Scholar
  11. 11.
    Yun, B.H., Baek, G.R., Bae, M.J. (eds.): A study on building SVDB to monitor a soft voice. Inst. Electron. Inf. Eng. 800–801 (2011)Google Scholar
  12. 12.
    Park, H.W., Bae, S.G., Bae, M.J. (eds.): Improving pitch search through emphasized harmonics. The Acoust. Soc. Korea, 230–232 (2012)Google Scholar
  13. 13.
    Ahn, I.-S., Bae, M.-J., Bae, S.-G.: A study on promoting appetite in sound signal processing. MAGNT Research Report 2(5), 105–109 (2014)Google Scholar
  14. 14.
    Lee, W.-H., Bae, S.-K., Bae, M.-J.: A study on low frequency noise analysis of dehumidifier using acoustic characteristics. In: Proceedings of 31st Annual Conference on Voice Communication and Signal Processing, vol. 145–146 (2014)Google Scholar
  15. 15.
    Hall, H., Jeon, J.-Y.: Allies, Do you cure illness with sound? The Sea Publishers, (Korea) Skeptic: promoting science and critical thinking vol. 1, pp. 8–15(2015)Google Scholar
  16. 16.
    Brannon, L., Paste, J., Han, D.-W.: Health Psychology. Sengei Learning Korea (2011)Google Scholar
  17. 17.
    Batsell W.R.,·Brown A.S.: Human flavor-aversion learning: a comparison of traditional aversions and cognitive aversions. Learn. Motiv. 29:383–396 (1998)CrossRefGoogle Scholar
  18. 18.
    Bae, Seong-Geon, Bae, Myung-Jin: A study on recovery in voice analysis through vocal changes before and after specch using speech signal processing. IJAER 12, 5299–5303 (2017)Google Scholar
  19. 19.
    Bae, S.G., Kim, M.S., Bae, M.J.: On enhancement signal using non-uniform sampling in clipped signals for LTE smart phones. In: 2013, IEEE ICCE-Berlin, pp. 125–126. ICCE-Berlin (2013)Google Scholar
  20. 20.
    Bae, M., Kim, M.: Professor Bae’s Sound Story. Gimm-Young Publishers, Inc (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ik-Soo Ahn
    • 1
  • Bong-Young Kim
    • 1
  • Kwang-Bock You
    • 1
  • Myung-Jin Bae
    • 2
  1. 1.Department of Information and TelecommunicationSoongsil UniversityDongjakSouth Korea
  2. 2.Department of Information and Telecommunication EngineeringSoongsil UniversityDongjakSouth Korea

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