Closed-loop control of a network of intra-muscular electrical microstimulators aiming for precise gestures: preliminary assays in New Zealand white rabbits

Abstract

Functional electrical stimulation consists of the delivery of electrical pulses aimed to restore functional movements in paralytic individuals. Its level of applicability is still highly dependent on the invasiveness of the systems required to perform multi-site stimulations. In this framework,

one of the most promising approaches is based on the deployment of wireless networks of intra- muscular microstimulators. However, up to date, this approach has been limited by the size of

the currently available microstimulators. Biomedical Electronics Research Group (BERG) at University Pompeu Fabra is pioneering the development of intra-muscular microstimulators with unprecedented features regarding minimal invasiveness. These devices have a diameter below 1 mm and most of their body is made up of flexible materials. These injectable flexible devices developed by BERG, known as eAXONs, evoke neuromuscular stimulations using the rectification of volume conducted high frequency (HF) current pulses supplied by an external unit. Several of these independent eAXONs microstimulators can form a network to be implanted and ultimately, digitally controlled. Until now, BERG has manufactured and validated its first functional prototypes. Nonetheless, their applicability to induce precise movements has still not been demonstrated. In this context is where the current Bachelor Thesis has its core hypothesis proposal: to prove that using a closed-loop controller and a network of implanted eAXONs it is possible to control certain precise muscular trajectories of 1 degree of freedom (DOF) in a New Zealand anesthetized rabbit. In order to find an appropriate deployment of these prototypes in a living organism, apart from the Simulink plant and the eAXONs technology, the thesis has integrated a 3D-printed exoskeleton architecture, a detailed stimulation protocol, a proper conditioning of the electronic system and the future lead of a predictive musculoskeletal model allowing for a deeper in-silico understanding of the evoked trajectories and the ultimate proof of the above mentioned core hypothesis.