An Adaptable Lateral Resolution Acoustic Beamforming for Network of
Wireless Neural Interfaces
- Hanna Firew ,
- Michael Barros
Abstract
Wireless Neural Interfaces are minimally invasive untethered links
between the brain tissue and silicon platforms. Even though these
interfaces have been envisioned for many biomedical applications, it is
unclear how the ultimate technology will be, due to the lack of studies
that support spatially distributed networks. In this paper, we
contribute to the first step towards a networked wireless neural
interfaces scenario by addressing the distributed power allocation
through adaptable beamforming by varying the acoustic beam lateral
resolution. Our technique provides selectivity and depthness of neural
interface nodes inside the Brain's neocortex. Our results show
improvements in average power transfer efficiency for sparser beams
compared to narrower ones for a randomly placed network of implantable
devices with 15 nodes within a 4mm2 space in the neocortex. Lateral
resolution indeed achieves selective of the devices, the average
efficiency was non-constant throughout the network allowing devices to
operate in different time scales suitable for asynchronous networks.
Enabling a functioning network is essential for providing an impactful
interface with the Brain to allow future usage of this technology in a
diverse set of neurological diseases theranostics.