2020 Fiscal Year Final Research Report
Motion sensory integration assist system for training motion and sensory function of deep muscles
| Project/Area Number |
17H03195
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent mechanics/Mechanical systems
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| Research Institution | Hokkaido University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
島谷 康司 県立広島大学, 保健福祉学部(三原キャンパス), 教授 (00433384)
栗田 雄一 広島大学, 先進理工系科学研究科(工), 教授 (80403591)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Keywords | 運動知覚アシスト / バイオフィードバック / 骨盤底筋トレーニング / 人間拡張 |
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| Outline of Final Research Achievements |
We have developed a wearable assist system for efficiently training motor and sensory functions by supporting the integration of movement and perception in deep muscles where movement perception is difficult. The pelvic floor muscle group (PFM) was treated as the deep muscle. We have developed an indirect motion teaching interface technology that utilizes PFM and muscle synergy of the abdominal lateral muscles and a wearable motion perception interface that uses force-tactile stimuli, and implemented them in a wearable system. We also designed a training program according to the individual's pelvic alignment. We conducted a subject experiment of PFM training using the developed motion perception assist system and verified its effectiveness.
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| Free Research Field |
ロボット工学，バイオメカニズム
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| Academic Significance and Societal Importance of the Research Achievements |
運動知覚が困難なPFMの効果的トレーニングのための運動知覚アシストシステムを開発した．トレーニング対象筋肉と筋シナジー関係にある筋肉の活動を用いて間接的にバイオフィードバックトレーニングを実現した．また，個人の骨盤アライメントを反映させた筋骨格動力学モデルにより，効果的なトレーニング姿勢を推定する手法を構築した．本研究成果は，特に女性に多く見られる腹圧性尿失禁患者の治療法である膣挿入型筋電を用いたPFMトレーニングに代わる画期的かつ効率的なトレーニング方法として活用が期待される．
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