Abstract
Learning and usability of a 3D modelling system depend on direct and indirect human-dependent factors. These factors need to be studied in order to design a state-of-the-art computer tool or software. In this paper, we have presented a novice/expert analysis of a 3D modelling system in which user used two different sets of inputs i.e. keyboard/mouse and speech/gesture to draw the 3D object in AutoCAD. To analyse the user's cognitive workload, we have used electroencephalography (EEG) signals and extracted various frequency bands and power spectral density (PSD) estimates. EEG signals and questionnaires were used to understand the user's behaviour. The results showed that users find i t d ifficult to dr aw a 3D object using the multi-modal input speech/gesture compared to keyboard/mouse. A significant change in theta and alpha bands activity was observed during the analysis. We found that novice users were relatively comfortable in using multi-modal interface system then the expert users which indicates that novice users can learn to use the multi-modal input more quickly then the expert users.
| Original language | English |
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| Title of host publication | 26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings |
| Publisher | IEEE |
| Number of pages | 7 |
| ISBN (Electronic) | 9781538678343 |
| DOIs | |
| Publication status | Published - 2 Jul 2018 |
| Event | 26th International Conference on Systems Engineering, ICSEng 2018 - Sydney, Australia Duration: 18 Dec 2018 → 20 Dec 2018 |
Publication series
| Name | 26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings |
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Conference
| Conference | 26th International Conference on Systems Engineering, ICSEng 2018 |
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| Country/Territory | Australia |
| City | Sydney |
| Period | 18/12/18 → 20/12/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- EEG
- Expert
- Expertise
- Gesture.
- HCI
- Multimodal Interface system
- Novice
- Speech