Alternative communication system for people with severe motor disabilities using myoelectric signal control
Abstract
We have now sufficient evidence that the use of bioelectric signals in the field of Augmented and Alternative Communication (AAC) is feasible. Moreover they are particularly suitable for people with severe motor disabilities, for example, people with high levels of spinal cord injury or with locked-in syndrome. The development of solutions for this kind of people implies in the finding of ways to use sensors that fit the user needs as well as the constrains involved, translating the intentions of the user in commands. This paper presents a human-computer interface (HCI), based on the acquisition of electromyographic (EMG) signals to interact with an Assistive Communication System (ACS). The developed tool was tested successfully by patients severely disabled by amyotrophic lateral sclerosis (ALS) and other diseases.