2022 Fiscal Year Final Research Report
Bayesian Model-based Rehabilitation
Project/Area Number |
20H04260
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Research Category |
Grant-in-Aid for Scientific Research (B)
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Allocation Type | Single-year Grants |
Section | 一般 |
Review Section |
Basic Section 61050:Intelligent robotics-related
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Research Institution | Tohoku University |
Principal Investigator |
Owaki Dai 東北大学, 工学研究科, 准教授 (40551908)
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Co-Investigator(Kenkyū-buntansha) |
関口 雄介 東北大学, 大学病院, 理学療法士 (60535095)
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Project Period (FY) |
2020-04-01 – 2023-03-31
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Keywords | 脳卒中 / 歩行 / 個別性 / 階層ベイズモデル / 最適かつ帰結予測 |
Outline of Final Research Achievements |
This study aimed to clarify the individuality of walking in stroke patients and achieve optimal rehabilitation for each patient. We conducted kinematic and kinetic analyses during walking using a three-dimensional motion analysis system and ground reaction force (GRF) measurement devices on 51 stroke patients with hemiplegia. As a result, principal component analysis (PCA) of the whole-body angular momentum (WBAM) revealed that only two principal components (PC1 and PC2) explained 95.3%±3.44 of the variance. Furthermore, an analysis that extracted commonality and individuality showed that the first PC of PC1 (PC1-PC1) of WBAM was a common component among all patients (similar to healthy subjects' PC) and the second PC of PC1 (PC1-PC2) represented individuality. Based on these results, a hierarchical Bayesian model will lead to the realization of rehabilitation providing optimal and predictable interventions for each patient.
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Free Research Field |
リハビリテーション
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Academic Significance and Societal Importance of the Research Achievements |
本研究の学術的意義は,脳卒中患者の歩行における個別性を解明し,最適なリハビリを実現するための基礎的な知見を提供することである.また,社会的意義としては,脳卒中は日本人の死因第4位,要介護になる要因の第1位であり,その治療やリハビリに関する研究は重要な社会的課題である.本研究では,階層ベイズモデルに基づく歩行診断により患者ごとの最適かつ帰結予測可能な介入法を提供することを目指しており,これにより脳卒中患者の生活の質向上や医療費削減などに繋がると期待される.
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