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Motion Primitive Segmentation Based on Cognitive Model in VR-IADL

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HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13095))

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Abstract

Recently, many studies have been conducted using virtual reality (VR) technology in the medical field. Our research group has been developing a virtual kitchen challenge (VKC), which is a system to evaluate instrumental activities of daily living (IADL) using VR technology. In the previous study, we focused on motion primitives, which are the smallest unit of motion in VKC. In this study, we focused on the motion of the VKC task when there is no contact with the screen and developed a model that can be segmented by motion primitives. Furthermore, using a two-step process based on time-series data of the subject's fingertip velocity during the VKC task, we developed a model that can be segmented in terms of motion primitives. Therefore, the segmentation accuracy was 83.4%, and the percentage of false positives was as high as 28%.In the future, we plan to revise the feature set.

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Acknowledgments

This work was supported by Grant-in-Aid for Scientific Research (C) 18K12118 and National Institute on Aging (NIA) R01AG062503.

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Authors and Affiliations

  1. Suwa University of Science, Toyohira, Chino, Nagano, 5000-1, Japan

    Taisei Ando & Takehiko Yamaguchi

  2. Tokyo University of Science, Yamazaki, Noda, Chiba, 2641, Japan

    Norito Kohama

  3. Saga University, 5-1-1 Nabeshima, Saga, Saga, Japan

    Maiko Sakamoto

  4. Temple University, Philadelphia, PA, 19122, USA

    Tania Giovannetti

  5. Tokyo University of Science, 6-3-1 Niijuku, Katsushika, Tokyo, Japan

    Tetsuya Harada

Authors
  1. Taisei Ando
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  2. Takehiko Yamaguchi
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  3. Norito Kohama
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  4. Maiko Sakamoto
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  5. Tania Giovannetti
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  6. Tetsuya Harada
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Corresponding author

Correspondence to Taisei Ando .

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Editors and Affiliations

  1. University of Creteand Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. The Open University of Japan, Chiba, Japan

    Masaaki Kurosu

  3. U.S. Army Research Laboratory, Aberdeen Proving Ground, MD, USA

    Jessie Y. C. Chen

  4. U.S. Army Combat Capabilities Development Command Soldier Center, Orlando, FL, USA

    Gino Fragomeni

  5. Smart Future Initiative, Frankfurt am Main, Hessen, Germany

    Norbert Streitz

  6. Faculty of Arts and Science, Kyushu University, Fukuoka, Japan

    Shin'ichi Konomi

  7. Siemens (United States), Princeton, NJ, USA

    Helmut Degen

  8. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Stavroula Ntoa

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Ando, T., Yamaguchi, T., Kohama, N., Sakamoto, M., Giovannetti, T., Harada, T. (2021). Motion Primitive Segmentation Based on Cognitive Model in VR-IADL. In: Stephanidis, C., et al. HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence. HCII 2021. Lecture Notes in Computer Science(), vol 13095. Springer, Cham. https://doi.org/10.1007/978-3-030-90963-5_17

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  • DOI: https://doi.org/10.1007/978-3-030-90963-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90962-8

  • Online ISBN: 978-3-030-90963-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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