1999 Fiscal Year Final Research Report Summary
Human Interface Design that considers Cognitive Characteristics
| Project/Area Number |
09838030
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
感性工学
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| Research Institution | Hiroshima City University |
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Principal Investigator |
MURATA Atsuo Hiroshima City University, Faculty of Information Science, Professor, 情報科学部, 教授 (10200289)
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| Project Period (FY) |
1997 – 1999
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| Keywords | human interface / cognitive load / visual interference / speech input / multimodal / functional visual field / dual task / mental workload |
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| Research Abstract |
In this study, the method of human interface design in tasks that needed cognitive information processing to a larger extent was discussed from viewpoints of proper cognitive loading, interference of cognitive information processing, and mental workload.
We investigated visual interference on multi-window systems. We also explored the monitoring characteristics of human operators when monitoring multiple instruments. From these two studies, it was clarified that the capacity of visual information decreased and the human error increased with the increase of the cognitive workload. Moreover, a method to measure the functional visual field was developed and the trade-off relationship between the depth and the width of visual information processing was quantitatively explored. We also found that the funneling effect occurred with the increase of cognitive loading at the foveal vision.
We made an attempt to evaluate mental workload induced by the increase of cognitive loading using a wavelet transform technique. As a result, the total power of θ, α and β frequency band and the appearance time of the maximum power were found to be effective and sensitive measures for the evaluation of mental workload.
The effectiveness of speech input in multimodal and multi-task environments was discussed from the viewpoint of decrease of cognitive workload. The speech input was found to decrease cognitive workload for both multimodal and multi-task environments. The problems when using speech input were also identified.
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