University of Illinois Urbana-Champaign

A Comparison of Speech, Touch, and SSVEP-Based BCI Inputs for Head-Mounted Displays

Choudhary, Ojasvi

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https://hdl.handle.net/2142/88904

Description

Title
A Comparison of Speech, Touch, and SSVEP-Based BCI Inputs for Head-Mounted Displays
Author(s)
Choudhary, Ojasvi
Contributor(s)
Bretl, Timothy
Issue Date
2015-12
Keyword(s)
  • head-mounted display
  • brain-computer interface
  • steady-state visual evoked potential
  • augmented reality
  • android
Abstract
We evaluated steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCI) as an input mechanism for head-mounted displays (HMDs). Our evaluation compared the performance of three input mechanisms on a Google Glass (speech recognition, touch gestures, and SSVEP) with SSVEP-based BCI on a desktop monitor. The results of this comparison study show that the SSVEP-based BCI on a desktop monitor can classify input commands with greater than 98% accuracy in an average of 1.23 seconds. Neither speech recognition nor touch gestures were found to be significantly faster. While SSVEP-based BCI on a Google Glass was significantly slower than SSVEP-based BCI on a desktop and touch gestures, it still achieved greater than 94% accuracy after 2.2 seconds. Our results show that SSVEP-based BCIs may provide an attractive input mechanism for HMDs and, in particular, suggest that there may be conditions under which SSVEP-based BCIs are comparable in performance to existing HMD input mechanisms.
Type of Resource
text
Language
en
Permalink
http://hdl.handle.net/2142/88904

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