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Browsing Computer Science and Informatics by Author "Dollman, Gavin John"
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Item Open Access Comparing brain-computer interfaces across varying technology access levels(University of the Free State, 2014) Dollman, Gavin John; De Wet, L.; Beelders, T. R.English: A brain-computer interface (BCI) is a device that uses neurophysiological signals measured from the brain to activate external machinery. BCIs have traditionally been used to enhance the standard of living for severely disabled patients. This has resulted in a shortage of data on how BCIs perform with able-bodied individuals. There has recently (2012) been a trend towards BCI research involving able users but these studies are still too few to make a substantial impact. Additionally, traditional input methods are being replaced or supplemented by alternative natural modes of interaction and these natural interactions have become known as NUIs. To investigate the suitability of a BCI as a NUI, this study used the Emotiv headset to provide direct measurement of a participant’s performance while performing tasks similar to wheelchair manipulation in order to determine whether a participant’s access to traditional input methods influences their performance. Thus, the main aim of this study was to investigate the usability of an Emotiv for robot navigation. Additionally, the study aimed to discover whether a user’s performance differed when using a keyboard compared to the Emotiv as well as investigating whether there was improvement of performance in the short term for a user through repetitive use of the Emotiv. In order to compare the usability of the Emotiv to a keyboard the participants were placed into groups based on their exposure to traditional input methods. This was verified based on their individual expertise rating, which was a measure of frequency and length of use. The test instrument used consisted of a written program that navigated a pair of Mindstorm NXT robots across a custom designed test course. Data was collected via usability testing which measured learnability, efficiency and effectiveness. Efficiency was measured as the time taken to complete a task while effectiveness was a measure of the errors made by a participant when completing a task. Results indicated that there was no significant difference between the groups’ efficiency and effectiveness when using the Emotiv to complete a task. Thus, a user’s previous experience with a traditional input method does not influence a user’s performance with an Emotiv when navigating a robot. This result indicates that the interface is intuitive to use and, therefore the Emotiv could be suitable as a NUI. The results for the usability metrics efficiency and effectiveness indicated that there was a significant difference between the performances with the Emotiv and a keyboard. The results show that, with the Emotiv, participants took more time to complete a task and made more errors when compared to a keyboard. This discrepancy was attributed to cognitive theory as it is believed that the participants violated their preformed schema which affected their performance. However, the participants quickly became comfortable with the Emotiv which supports the evidence that the interface is intuitive to use. For neither the usability metrics efficiency nor effectiveness was a significant improvement detected with repetitive use of the Emotiv. Thus, repetitive use of the Emotiv to navigate a robot does not improve a user’s performance over a short period of time. These results indicate that in terms of efficiency and effectiveness the keyboard is the superior interface. The results also revealed that a participant’s performance is not affected by their exposure to traditional input methods when utilising a BCI. Thus, the Emotiv is intuitive to use and appears suitable for use as a NUI. This study proved that the Emotiv is an intuitive interface and can be used with little to no previous experience.