Multi-modal target prediction

Abstract

Users with severe motor impairment often depends on alternative input devices like eye-gaze or head movement trackers to access computers. However these devices are not as fast as computer mouse and often turn difficult to use. We have proposed a Neural-network based model that can predict pointing target by analyzing pointing trajectory. We have validated the model for standard computer mouse, eye-gaze and head movement trackers. The model is used to develop an adaptation system that can statistically significantly reduce pointing times. © 2014 Springer International Publishing.