| Project/Area Number |
16K12462
|
|---|
| Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Perceptual information processing
|
|---|
| Research Institution | Kyoto University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2016-04-01 – 2019-03-31
|
| Project Status |
Completed (Fiscal Year 2018)
|
| Budget Amount *help |
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
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)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
|
|---|
| Keywords | 瞳孔計測 / 画像計測 / 内部状態計測 / 瞳孔径 / 可視光 / 周波数領域 / 集中度 / 高周波 / 人間計測 |
|---|
| Outline of Final Research Achievements |
In this study, we developed a method to estimate human task concentration using pupil size (diameter). Although it is well known that the pupil diameter changes depending on the intensity of incident light, it is also affected by changes in the internal state of the person. In other words, although it is theoretically possible to obtain the internal state of a person from pupil diameter change, it is not used as a sensing device in a real environment. Through this research, we designed Target Pointing task (hereinafter referred to as "TP task") with variable path width / path length constraint, and made it possible to change the degree of difficulty of the task. Moreover, this task enables to study how the pupil system of a person changes when the task difficulty level is changed variously. From here, we could obtain a model for the change in difficulty of the TP task and the change in pupil diameter, and derived a model for the change in pupil diameter and the TP task.
|
| Academic Significance and Societal Importance of the Research Achievements |
瞳孔径変化を人の内部状態推定に用いることはすでに提案されていたが，タスクの難易度と瞳孔径変化の関係を定量的に示した過去の研究は実用化に乏しかった．これに対し，我々はTPタスク自体に問題があると考えて，新たに可変経路幅／経路長制約を持つTPタスクを提案した．これにより，従来のTPタスクでは繰り返しによる実験でしか変化が見いだせなかったものを，１回の試行で再現可能にした．これを用いて，瞳孔径の変化から内部状態（特に集中）と瞳孔径変化の関係を明らかにしタスク難易度／瞳孔径関連モデルを導出した．これにより,ゲームの評価や車運転時の危機管理等への応用が期待できる.
|
