Neuroprosthetic interfaces require light-weighted and power-optimized systems that combine acquisition and stimulation together with a computational unit capable to perform on-line analysis for closed-loop control. Here, we present an ultra-compact and low-power system able to acquire from 32 channels and stimulate independently using both current and voltage. The system has been validated in vivo for rats in the recording of spontaneous and evoked potentials and peripheral nerve stimulation, and it was tested to reproduce the muscular activity involved in gait. This device has potential application in long-term clinical therapies for the restoration of limb control and it can become a development platform for closed loop algorithms in neuromuscular interfaces.
11 Sep 2017
International Conference on Artificial Neural Networks