EYE INTERACTION BASED ON LOW COST CAMERAS TO SUPPORT THE COMMUNICATION OF INDIVIDUALS WITH AMYOTROPHIC LATERAL SCLEROSIS
Eye Tracking; Computer vision; Artificial intelligence; Motor Neuron Disease; Amyotrophic Lateral Sclerosis (ALS);
In the context of Amyotrophic Lateral Sclerosis (ALS), a neurodegenerative disease that progressively and irreversibly affects an individual's motor neurons, quality of life is one of the main factors that impact survival. Aspects such as multidisciplinary care (palliative care), physical and psychological well-being, respiratory care and assistive technology resources are part of the ecosystem that provides a better quality of life. With the inevitable progression and impairment of the motor system of individuals with ALS, impairments in functional abilities arise and, for example, the communicative process, autonomy and social interaction or participation are partially or fully affected. To compensate for these losses and allow Human-Computer Interaction (HCI), there are different approaches in the literature, such as those based on electroencephalography (EEG) - the so-called Brain Computer Interface (BCI), electromyography (EMG), electrooculogram (EOG) ) and through cameras or images. Considering Alternative Communication (AC) systems in a home environment, the camera approach is the most suitable. In this context, part of this work is the proposal of an experimental study for the creation of an IHC module for real-time eye tracking based on low-cost non-infrared cameras, as well as objects attached to the head of the individual with ALS, and algorithmic models of Machine Learning (AM). The real-time eye tracking module should be integrated with the CA Autonomus software ecosystem, developed by the Laboratory for Technological Innovation in Health (LAIS) of the Federal University of Rio Grande do Norte (UFRN).