| Project/Area Number |
16K16468
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Rehabilitation science/Welfare engineering
|
|---|
| Research Institution | Tokyo University of Science, Suwa (2017)
Tokyo University of Science (2016) |
|---|
Principal Investigator |
|
|---|
| Research Collaborator |
Giovannetti Tania テンプル大学, 心理学科, 准教授
|
|---|
| Project Period (FY) |
2016-04-01 – 2018-03-31
|
| Project Status |
Completed (Fiscal Year 2017)
|
| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
|
|---|
| Keywords | MCI早期発見 / VR-IADL / 行動特徴解析 / Virtual Reality / Micro-error / マイクロエラー / 行動特徴量 / 行動認識技術 / 軽度認知障害 / 行動特徴量解析 / 医療・福祉 / 人間生活環境 / 情報工学 / 機械学習 |
|---|
| Outline of Final Research Achievements |
In this research, we aimed to develop a model to identify error behaviors during VR-IADL task. Specifically, we developed a proposed model using information on hand behavior and gaze behaviors in tasks measured in the IADL task environment constructed using VR technology. In the development of the proposed model, we solved the following two problems. (1) Quantification of OE, CE, ME actions, gaze behaviors of MCI patients in IADL task, (2) Effective feature quantities selected from quantified OE, CE, ME.
|
