The authors describe the creation of the VAHM prototype, including the hardware and software functionalities and other aspects of this "smart" wheelchair.

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.

The VAHM project aims to improve the control of powered wheelchairs by adding possibilities of autonomous mobility. We propose specifications which are based on a detailed study of similar projects described in specialized publications. Three operating modes are defined in order to adapt the system to a great diversity of situations. In the autonomous mode a global trajectory is planned, and the user then intervenes to point the goal and, if need be, stop a motion during its execution. The assisted manual mode allows access to local primitives like a wall following. Finally, in the manual mode, we find the classical control of a powered wheelchair again. The first results of the technical evaluation are discussed in the conclusion.

In this paper, an assessment of a driving assistance by a deictic command for a smart wheelchair is proposed. This equipment enables the user to move with a series of indications on an interface displaying a view of the environment and bringing about automatic movement of the wheelchair. Two sets of tests were implemented to assess the advantages of this type of assistance compared with conventional wheelchair control. The first set evaluated the performance of the human-machine system that is based on a course time analysis, an observation of users' actions, and an estimation of driving comfort. The second test was implemented to assess the cognitive requirements of the driving task, specifically the attentional and executive processes required when driving in assisted mode. A dual-task method was used to achieve this. The results show that driving assistance brings about a decrease in physical load for the same level of comfort as manual driving, but requires an additional cognitive effort for the user, especially in terms of executive abilities.