| Project/Area Number |
17K09219
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Hygiene and public health
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| Research Institution | Yonago National College of Technology |
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Principal Investigator |
NAKAYAMA Shigeki 米子工業高等専門学校, その他部局等, 教授 (90300607)
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| Co-Investigator(Kenkyū-buntansha) |
竹田 伸也 鳥取大学, 医学(系)研究科(研究院), 准教授 (00441569)
岩田 正明 鳥取大学, 医学部, 准教授 (40346367)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | うつ病 / スクリーニング / サブタイプ分類 / タブレット端末 / ウェアラブル端末 |
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| Outline of Final Research Achievements |
In this study, we have developed applications software for screening depression based on BDI test and executed screening test against some subjects. Then, we have detected walking posture of some subjects and estimated the angle of looking-down posture. In addition, we have counted the number of blinking by eyeglasses type wearable device. Finally, We have learned mental and physical information about subjects by Self-organization Map(SOM). We have confirmed that the symptoms of subject can be predicted by inputting unlearned subject data to learned SOM.
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| Academic Significance and Societal Importance of the Research Achievements |
BDIのスクリーニング結果と，ウェアラブル端末により検出した歩行時の俯き角度，そして一定時間での瞬き回数を多次元データとして学習することで，精神状態と身体状態の関係性を2次元マップ上に表現することが可能となった．自己組織化マップで扱う学習データを更に充実させることで，本研究はこれまでに困難とされているうつ病のサブタイプ分類の実現に大きく貢献する可能性を有する．
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