Tracking head movement for augmentative and alternative communication

Resumen

The use of computers as a communication tools is trivial nowadays, but the use of the PC by a impaired person is often a challenge. Augmentative and alternative communication (AAC) devices can empower these subjects by the use of their remaining functional movements, including head movements. Currently computer vision AAC solutions present limited performance in the presence of involuntary body movement or spasticity (stiff or rigid muscles). Our work proposes a novel human computer interface (HCI) based on the functional head movements of each user. After calibration, a Hidden Markov Model (HMM) classifier represents the desired functional movement based on the velocities components of the estimated head position. New segmented movements are then classified in valid or invalid based on the HMM. Valid segments can generate mouse “click” events that can be used with scanning virtual keyboards, enabling text editing, and within scanning based software that can control mouse functions.