dc.contributor.author | Deivasigamani, Hariprashanth | |
dc.date.accessioned | 2022-11-04T13:38:23Z | |
dc.date.available | 2022-11-04T13:38:23Z | |
dc.date.issued | 2022-11-03 | |
dc.identifier.uri | http://hdl.handle.net/10222/82063 | |
dc.description.abstract | Over-plotting and screen size are issues that challenge multivariate data visualization, even on large displays. Large datasets make scrolling through data tedious, and pose difficulties in isolating data points. Multivariate datasets can require displaying multiple graphs, which incurs cognitive load for the user when context switching between graphs. A hybrid tablet + augmented reality (AR) interface can visualize large data in AR beyond the boundaries of the conventional screen, which may permit effective multivariate data visualization. In this research I designed and evaluated a hybrid tablet and head-worn AR interface to visualize multivariate Brain-Computer Interface (BCI) time-series data. I explored two techniques for combining a head-worn AR display with a tablet display for information visualization: rendering 2D AR content in layers above the tablet display, and rendering 2D AR content around and on the same visual plane as the tablet display. I conducted a controlled within-subjects experiment to comparatively evaluate the above display and around display AR interfaces against a tablet-only interface. In the above-display experiment, multivariate time-series data is presented in four AR layers above the display. In the around-display experiment a long duration time series extends beyond the edges of the display. I collected task accuracy and time to complete tasks as primary measures. Semi-structured interviews, self-reported usability and task load scores, and custom questionnaire responses are collected for interface feedback. Above display AR yielded significantly higher task accuracy but more time taken for task completion than the tablet only interface when looking through the four horizontal AR layers in a standing position. Around display AR yielded significantly higher task accuracy than the tablet only interface and similar time taken to complete tasks. Still, participants expressed numerous reservations about the hybrid setup, including higher task load and lower perceived usability vs. the tablet only configuration. | en_US |
dc.language.iso | en | en_US |
dc.subject | Augmented Reality (AR) | en_US |
dc.subject | Brain Computer Interface (BCI) | en_US |
dc.subject | Human Computer Interaction (HCI) | en_US |
dc.title | ARTIV BCI: AUGMENTED REALITY + TABLET INTERFACE FOR VISUALIZING BRAIN COMPUTER INTERFACE DATA | en_US |
dc.date.defence | 2022-09-28 | |
dc.contributor.department | Faculty of Computer Science | en_US |
dc.contributor.degree | Master of Computer Science | en_US |
dc.contributor.external-examiner | n/a | en_US |
dc.contributor.graduate-coordinator | Dr. Michael McAllister | en_US |
dc.contributor.thesis-reader | Dr. Rina Wehbe | en_US |
dc.contributor.thesis-reader | Dr. Stephen Brooks | en_US |
dc.contributor.thesis-supervisor | Dr. Derek Reilly | en_US |
dc.contributor.ethics-approval | Received | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.copyright-release | Not Applicable | en_US |