Current active leg prostheses do not integrate the most recent advances in Brain-Computer Interfaces (BCI) and bipedal robotics. Moreover, their actuators are seldom driven by the subject’s intention. In this paper, we propose an original and biologically-inspired leg prosthesis control scheme, which brings together these three aspects. It is composed of an EOG-based eye tracker and a Programmable Central Pattern Generator (PCPG). In a first step, specific sequences of eye movements executed by the user are identified by the eye tracking system. These sequences are then converted to high-level commands (such as accelerate, decelerate or stop) and sent to the prosthesis actuator control unit. In this unit, a PCPG is implemented, which is able to model human walk in a perfectly periodic way. One of the main interests of that tool is the possibility to modify the gait pattern to adapt to different walking speeds in a smooth way. Several results from previous studies are summarized and discussed in order to demonstrate the feasibility of such a system.

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