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Central pattern generators (CPGs) are known to play an important role in the generation of rhythmic movements in gait, both in animals and humans. The comprehension of their underlying mechanism has led to the development of an important family of algorithms at the basis of autonomous walking robots. Recently, it has been shown that human gait could be modeled using a subclass of those algorithms,...
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...
In this paper, we propose an original and biologically-inspired leg prosthesis control system. We demonstrate that human walk periodic patterns can be modeled by a Programmable Central Pattern Generator (PCPG) algorithm. Assuming that high-level commands reflecting the user's intention (such as accelerate, decelerate or stop) — and optionally, with their associated confidence level — are available,...
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