Brain wave measurement while touching task of a virtual arm for intuitive robotic surgery

Satoshi Miura, Junichi Takazawa, Yo Kobayashi, Tomoyuki Miyashita, Masakatsu G. Fujie, Kazuya Kawamura

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper presents a novel evaluation method for designing an intuitive surgical robot by measuring a user's brain activity. Conventionally, surgical robots have been designed based on their mechanical performance. However, an improvement in a robot's mechanical performance does not necessarily represent the embodiment that the user feels. In this paper, we evaluate intuitive operability based on the user's brain activation. Previously, we used functional near-infrared spectroscopic-topography (fNIRS) brain imaging; however, it is better to use a brain measurement technique possessing a high time resolution, as brain activity is has a higher time resolution than fNIRS. The objective was to measure changes in brain activity as a function of a change in the slave arm positioning. In the experiment, the brain activity of four participants was measured using fNIRS while they used a hand controller to move the virtual arm of a surgical simulator. The experiment was carried out with the virtual arm in two positions: one easy to control and the other difficult. The spectrum of the brain activity increased at the easy position more than at the difficult position. We conclude that the brain activity changed as the user perceived that the virtual arm belonged to their body.

    Original languageEnglish
    Title of host publication2016 World Automation Congress, WAC 2016
    PublisherIEEE Computer Society
    Volume2016-October
    ISBN (Electronic)9781889335513
    DOIs
    Publication statusPublished - 2016 Oct 4
    Event2016 World Automation Congress, WAC 2016 - Rio Grande, United States
    Duration: 2016 Jul 312016 Aug 4

    Other

    Other2016 World Automation Congress, WAC 2016
    CountryUnited States
    CityRio Grande
    Period16/7/3116/8/4

    Fingerprint

    Brain
    Topography
    Infrared radiation
    Robotic surgery
    Simulators
    Experiments
    Chemical activation
    Robots
    Imaging techniques
    Controllers

    Keywords

    • EEG
    • fNIRS
    • Robotic Surgery
    • tele-operation

    ASJC Scopus subject areas

    • Control and Systems Engineering

    Cite this

    Miura, S., Takazawa, J., Kobayashi, Y., Miyashita, T., Fujie, M. G., & Kawamura, K. (2016). Brain wave measurement while touching task of a virtual arm for intuitive robotic surgery. In 2016 World Automation Congress, WAC 2016 (Vol. 2016-October). [7582953] IEEE Computer Society. https://doi.org/10.1109/WAC.2016.7582953

    Brain wave measurement while touching task of a virtual arm for intuitive robotic surgery. / Miura, Satoshi; Takazawa, Junichi; Kobayashi, Yo; Miyashita, Tomoyuki; Fujie, Masakatsu G.; Kawamura, Kazuya.

    2016 World Automation Congress, WAC 2016. Vol. 2016-October IEEE Computer Society, 2016. 7582953.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Miura, S, Takazawa, J, Kobayashi, Y, Miyashita, T, Fujie, MG & Kawamura, K 2016, Brain wave measurement while touching task of a virtual arm for intuitive robotic surgery. in 2016 World Automation Congress, WAC 2016. vol. 2016-October, 7582953, IEEE Computer Society, 2016 World Automation Congress, WAC 2016, Rio Grande, United States, 16/7/31. https://doi.org/10.1109/WAC.2016.7582953
    Miura S, Takazawa J, Kobayashi Y, Miyashita T, Fujie MG, Kawamura K. Brain wave measurement while touching task of a virtual arm for intuitive robotic surgery. In 2016 World Automation Congress, WAC 2016. Vol. 2016-October. IEEE Computer Society. 2016. 7582953 https://doi.org/10.1109/WAC.2016.7582953
    Miura, Satoshi ; Takazawa, Junichi ; Kobayashi, Yo ; Miyashita, Tomoyuki ; Fujie, Masakatsu G. ; Kawamura, Kazuya. / Brain wave measurement while touching task of a virtual arm for intuitive robotic surgery. 2016 World Automation Congress, WAC 2016. Vol. 2016-October IEEE Computer Society, 2016.
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