Emotional data visualization for well-being, based on HRV analysis

Akane Matsumae, Ruiyao Luo, Yun Wang, Eigo Nishimura, Yuki Motomura

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

    2 Citations (Scopus)


    Managing negative emotions and promptly relieving anxiety are two main focuses in the prevention of mental illness. This paper indicates a biofeedback-training experience that helps an experiencer to manage his/her emotions. The authors have defined the following major problems to approach this bio-feedback design procedure. The first one is how to grasp human emotions using existing technologies in exhibition circumstances. The second one is what kind of manifestation should be used to create emotional resonance. For the first problem, Heart Rate Variability (HRV) is adopted to obtain anxiety and stress levels. For the second problem, the authors took a nature-inspired design approach. The results are visualized on a wall composed of 64 bionic scales. A device system guides the experiencer into a meditative state, and contributes to spurring thoughts on emotional management, and thus achieving the purpose of preventing mental illness.

    Original languageEnglish
    Title of host publicationIntelligent Human Systems Integration
    Subtitle of host publicationIntegrating People and Intelligent Systems
    EditorsTareq Ahram, Waldemar Karwowski, Alberto Vergnano, Francesco Leali, Redha Taiar
    Number of pages7
    ISBN (Print)9783030395117
    Publication statusPublished - 2020
    Event3rd International Conference on Intelligent Human Systems Integration, IHSI 2020 - Modena, Italy
    Duration: Feb 19 2020Feb 21 2020

    Publication series

    NameAdvances in Intelligent Systems and Computing
    Volume1131 AISC
    ISSN (Print)2194-5357
    ISSN (Electronic)2194-5365


    Conference3rd International Conference on Intelligent Human Systems Integration, IHSI 2020

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Computer Science(all)


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