We have now sufficient evidence that using electrical biosignals in the field of Alternative and Augmented Communication is feasible. Additionally, they are particularly suitable in the case of people with severe motor impairment, e.g. people with high-level spinal cord injury or with locked-up syndrome. Developing solutions for them implies that we find ways to use sensors that fit the user's needs and limitations, which in turn impacts the specifications of the system translating the user's intentions into commands. After devising solutions for a given user or profile, the system should be evaluated with an appropriate method, allowing a comparison with other solutions. This paper submits a review of the way three bioelectrical signals - electromyographic, electrooculographic and electroencephalographic - have been utilised in alternative communication with patients suffering severe motor restrictions. It also offers a comparative study of the various methods applied to measure the performance of AAC systems.

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Our aim is to implement a force feedback joystick on a powered wheelchair provided with a set of range sensors. This system is intended to people with disability for whom a traditional joystick control (or any other adapted sensor control) is difficult or impossible because of too severe motor disabilities. The force feedback is calculated according to the proximity of the obstacles and helps the user, without forcing him, to move towards the free direction. Adopted methodology aims at circumventing certain obstacles which slow down the diffusion and thus the current use of smart wheelchairs: problems of safety, of reliability and of acceptability in particular. The results presented aim at identifying the driving situations for which an assisted control can really improve the piloting performances compared to a traditional manual control.

The powered wheelchair (PW) has become an essential mobility assistive technology for people with motor disabilities. A critical step involved in maximizing the end-user experience is evaluating individual functional abilities. Using powered wheelchair simulation for driving analysis offers flexibility for safely evaluating the individual's driving performance in a variable environment and situations ranging in difficulty. Additionally, it makes it possible to measure numerous variables involved in the driving process. The main objectives of this pilot study were to assess PW users' outdoor driving abilities to study how the simulator can improve outdoor driving task performance, and to define new objective criteria for evaluating the overall driving process. The study presented involved a group of 12 children and young adults diagnosed with cerebral palsy. Simulations were conducted using ViEW (Virtual Electrical Wheelchair), a 3D wheelchair simulator designed in our laboratory. A customized virtual environment was designed to immerse the user in a life-like driving experience. We used the data collected on the simulator to define driving skills indicators. The acquired skills during simulations were transferable to on-road wheelchair driving. The participants' performance indicators produced positive results. Computed performance indicators can be a valuable decision-making tool for occupational therapists.

For some people with motor disabilities and speech disorders, the only way to communicate and to have some control over their environment is through the use of a controlled scanning system operated by a single switch. The main problem with these systems is that the communication process tends to be exceedingly slow, since the system must scan through the available choices one at a time until the desired message is reached. One way of raising the speed of message selection is to optimize the elementary scanning delay in real time so that it allows the user to make selections as quickly as possible without making too many errors. With this objective in mind, this article presents a method for optimizing the scanning delay, which is based on an analysis of the data recorded in "log files" while applying the EDiTH system [Digital Teleaction Environment for People with Disabilities]. This analysis makes it possible to develop a human-machine interaction model specific to the study, and then to establish an adaptive algorithm for the calculation of the scanning delay. The results obtained with imposed scenarios and then in ecological situations provides a confirmation that our algorithms are effective in dynamically adapting a scan speed. The main advantage offered by the procedure proposed is that it works on timing information alone and thus does not require any knowledge of the scanning device itself. This allows it to work with any scanning device.