Japanese Journal of Biofeedback Research
Online ISSN : 2432-3888
Print ISSN : 0386-1856
Volume 47 , Issue 1
Showing 1-8 articles out of 8 articles from the selected issue
Foreword
Symposium
  • Morihiro TSUJISHITA
    2020 Volume 47 Issue 1 Pages 3
    Published: 2020
    Released: November 13, 2020
    JOURNALS FREE ACCESS
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  • Yoichi NAGASHIMA
    2020 Volume 47 Issue 1 Pages 5
    Published: 2020
    Released: November 13, 2020
    JOURNALS FREE ACCESS
  • Risa SUZUKI
    2020 Volume 47 Issue 1 Pages 7-14
    Published: 2020
    Released: November 13, 2020
    JOURNALS FREE ACCESS

      Currently, many electromyographs in Japan are used for diagnosis and research purposes and are difficult to manipulate for ordinary users. If the electromyograph becomes a familiar tool, electromyogram information can be used as a common language for exercise guidance, and electromyogram biofeedback using them in daily life. Besides, it is expected that it can be used in various situations such as exercise for health promotion, sports, preventive medicine, and rehabilitation in the community. In this symposium, the introduction of low-cost simple electromyographs that can be manufactured using mobile terminals such as smartphones were presented.

      Next, the results of its validity and reliability tests, application examples in clinical settings, and educational settings were showed. In this way, it is expected that simple electromyographs by using an existing smartphone as a monitor will become popular as a familiar measurement tool in Japan. Also, using low-cost devices such as low-cost simple electromyographs that are easy to reach for users, I hope that the time will come when “visualization” will be made, and quantitative exercise guidance will be implemented.

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  • Masaki TERUOKA
    2020 Volume 47 Issue 1 Pages 15-18
    Published: 2020
    Released: November 13, 2020
    JOURNALS FREE ACCESS

      I gave as a discussant at the 47th Annual Meeting of the Biofeedback Society of Japan, and I publish my manuscript the latest version.

      Note, this paper is only a manuscript for the presentation, some inaccurate expressions that prioritize comprehensibility, or a columns by informal expressions are described, sorry.

      The main remarks are as follows,

    1 Instead of my self-introduction (Latest development example).

     (1) The development of a biosensors to be worn on an abdomen.

     (2) Why “AI” Device Rsch Lab.?

    2 What is “EEG” ?

    3 The methods of recent EEG analysis.

     (1) Graph theory

     (2) Topological data analysis (TDA)

     (3) Deep learning

    4 The future EEG analysis methods and Biofeedback.

     (1) Default Mode Network (DMN)

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