Date of this Version
2008
Document Type
Article
Abstract
This study developed an adaptive real-time humancomputer interface (HCI) that serves as an assistive technology tool for people with severe motor disability. The proposed HCI design uses eye gaze as the primary computer input device. Controlling the mouse cursor with raw eye coordinates results in sporadic motion of the pointer because of the saccadic nature of the eye. Even though eye movements are subtle and completely imperceptible under normal circumstances, they considerably affect the accuracy of an eye-gaze-based HCI. The proposed HCI system is novel because it adapts to each specific user’s different and potentially changing jitter characteristics through the configuration and training of an artificial neural network (ANN) that is structured to minimize the mouse jitter. This task is based on feeding the ANN a user’s initially recorded eye-gaze behavior through a short training session. The ANN finds the relationship between the gaze coordinates and the mouse cursor position based on the multilayer perceptron model. An embedded graphical interface is used during the training session to generate user profiles that make up these unique ANN configurations. The results with 12 subjects in test 1, which involved following a moving target, showed an average jitter reduction of 35%; the results with 9 subjects in test 2, which involved following the contour of a square object, showed an average jitter reduction of 53%. For both results, the outcomes led to trajectories that were significantly smoother and apt at reaching fixed or moving targets with relative ease and within a 5% error margin or deviation from desired trajectories. The positive effects of such jitter reduction are presented graphically for visual appreciation.
Recommended Citation
Sesin, Anaelis; Adjouadi, Malek; Cabrerizo, Mercedes; Ayala, Melvin; and Barreto, Armando, "Adaptive eye-gaze tracking using neural-network-based user profiles to assist people with motor disability" (2008). Electrical and Computer Engineering Faculty Publications. 28.
https://digitalcommons.fiu.edu/ece_fac/28
Rights Statement
No Copyright - United States. URI: http://rightsstatements.org/vocab/NoC-US/1.0/
The organization that has made the Item available believes that the Item is in the Public Domain under the laws of the United States, but a determination was not made as to its copyright status under the copyright laws of other countries. The Item may not be in the Public Domain under the laws of other countries. Please refer to the organization that has made the Item available for more information.
Comments
Originally published in Journal of Rehabilitation Research & Development