Eye-gaze as a form of human machine interface holds great promise for improving the way we interact with machines. Eye-gaze tracking devices that are non-contact, non-restrictive, accurate and easy to use will increase the appeal for including eye-gaze information in future applications. The system we have developed and which we describe in this paper… (More)
The precision of point-of-gaze (POG) estimation during a fixation is an important factor in determining the usability of a noncontact eye-gaze tracking system for real-time applications. The objective of this paper is to define and measure POG fixation precision, propose methods for increasing the fixation precision, and examine the improvements when the… (More)
A novel approach is presented for using an eye tracker-based reference instead of EOG for methods that require an EOG reference to remove ocular artifacts (OA) from EEG. It uses a high-speed eye tracker and a new online algorithm for extracting the time course of a blink from eye tracker images to remove both eye movement and blink artifacts. It eliminates… (More)
We propose a novel metric for quantitatively evaluating ocular artifact (OA) removal methods on real electroencephalogram (EEG) data. For real EEG, existing metrics measure the amount of artifact removed. Our metric measures how much a given method is likely to distort the underlying EEG. The new metric was used to evaluate two existing OA removal… (More)
An ultralight manual wheelchair that allows users to independently adjust rear seat height and backrest angle during normal everyday usage was recently commercialized. Prior research has been performed on wheelchair tilt, recline, and seat elevation use in the community, however no such research has been done on this new class of manual ultralight… (More)
A power spectral analysis study was conducted to investigate the effects of using an electromagnetic motion tracking sensor on an electroencephalogram (EEG) recording system. The results showed that the sensors do not generate any consistent frequency component(s) in the power spectrum of the EEG in the frequencies of interest (0.1-55 Hz).