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Title: | U-mind : understanding the user's state of mind using BCIs |
Authors: | Saliba, Kenneth (2012) |
Keywords: | Brain-computer interfaces User interfaces (Computer systems) Graphical user interfaces (Computer systems) |
Issue Date: | 2012 |
Citation: | Saliba, K. (2012). U-mind : understanding the user's state of mind using BCIs (Bachelor's dissertation). |
Abstract: | A focus shift towards "healthy" subjects has recently increased in the exploration of Brain-Computer Interaction. Researchers are currently addressing the effects of utilizing the novel input modality to try to control practically everything, from a simple game, to robot controlling prostheses. Until recently, BCIs where mostly designed for clinical and research purposes only. This was partly due to the size and complexity of the equipment involved. A new generation of BCIs has been introduced for the video game industry. What if apart from gaming these tools were to be used as an assessment tool? This dissertation will look at understanding the user's state of mind through a commercial BCI reading directly from the brain without having to correlate to particular body postures or gaze activity to determine attention levels. These results will be used to improve on various methods of gauging levels of attention. Tests will be carried out on participants during a session of job training. Results captured will be stored and analysed in order to assess the participant's level of attention during these training sessions. Participants will be asked to fill in a questionnaire related to the training session identifying which part was the most appealing. The results obtained will be correlated with the readings monitored. Apart from deciphering the state of mind during these sessions, the candidates will be further gauged during a final test. The results of this will be compared to the initial readings in order to confirm the original conclusions obtained. Ultimately the study has shown that one can score a high level of attention but it is very difficult to determine exactly on what the participant was actually paying attention to. |
Description: | B.SC.ICT(HONS)ARTIFICIAL INTELLIGENCE |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/92533 |
Appears in Collections: | Dissertations - FacICT - 2012 Dissertations - FacICTAI - 2002-2014 |
Files in This Item:
File | Description | Size | Format | |
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B.SC.(HONS)ICT_Saliba_Kenneth_2012.PDF Restricted Access | 10.64 MB | Adobe PDF | View/Open Request a copy | |
Saliba_Kenneth_acc.material.pdf Restricted Access | 65.13 kB | Adobe PDF | View/Open Request a copy |
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