An implantable neural interface with electromagnetic stimulation capabilities.

Invasive interfaces with the Peripheral Nervous System (PNS), which currently rely on electric means for both nerves stimulation and signals recording, are needed in a number of applications, including prosthetics and assistive technologies. Recent studies showed that the quality of the signal-to-noise ratio of the afferent channel might be negatively affected by physiological reactions, including fibrosis. In this paper we propose a novel approach to the development of implantable neural interfaces, where the PNS is excited electromagnetically and in situ, while electrical means are used only for neural signals recording. Electromagnetic (EM) waves, capable of overcoming fibrotic capsules, are generated by microfabricated coils. Stimulation coils and registration electrodes are deposited on the same flexible substrate, also provided with a bio-absorbable coating, which releases anti-fibrotic drugs and neurons-specific functionalized magnetic nanoparticles (NPs). The NPs are intended to improve the capability of local EM waves to elicit membranes depolarization, thus enhancing selectivity. This paper details the concept of the proposed technology and provides a preliminary in silico feasibility study.

Optimization of kinetic energy harvesters design for fully implantable Cochlear Implants.

Fully implantable Cochlear Implants (CIs) would represent a tremendous advancement in terms of quality of life, comfort and cosmetics, for patients with profound sensorineural deafness. One of the main challenges involved in the development of such implants consists of finding a power supply means which does not require recharging. To this aim an inertial Energy Harvester (EH), exploiting the kinetic energy produced by vertical movements of the head during walking, has been investigated. Compared to existing devices, the EH needs to exploit very low frequency vibrations (<2.5 Hz) with small amplitude (<9 m/s(2)). In order to maximize the power transduced, an optimization method has been developed, which is the objective of this paper. The method consists in calculating the dynamical behavior of the EH using discrete transforms of experimentally measured acceleration profiles. It is shown that the quick integration of the second order dynamical equation allows the use of computationally intensive optimization techniques, such as Genetic Algorithms (GAs). The robustness of the solution is also evaluated.