Analytical Modeling of a Communication Channel Based on Subthreshold Stimulation of Neurobiological Networks

Authors

Alireza Khodaei, University of Nebraska - LincolnFollow

First Advisor

Massimiliano Pierobon

Date of this Version

Fall 12-1-2017

Citation

A. Khodaei, "Analytical Modeling of a Communication Channel Based on Subthreshold Stimulation of Neurobiological Networks," University of Nebraska-Lincoln Digital Commons

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Master of Science, Major: Computer Science, Under the Supervision of Professor Massimiliano Pierobon. Lincoln, Nebraska: December, 2017

Copyright © 2017 Alireza Khodaei

Abstract

The emergence of wearable and implantable machines manufactured artificially or synthesized biologically opens up a new horizon for patient-centered health services such as medical treatment, health monitoring, and rehabilitation with minimized costs and maximized popularity when provided remotely via the Internet. In particular, a swarm of machines at the scale of a single cell down to the nanoscale can be deployed in the body by the non-invasive or minimally invasive operation (e.g., swallowing and injection respectively) to perform various tasks. However, an individual machine is only able to perform basic tasks so it needs to exchange data with the others and outside world through an efficient and reliable communication infrastructure to coordinate and aggregate their functionalities. We introduce in this thesis Neuronal Communication (NC) as a novel paradigm for utilizing the nervous system \emph{in vivo} as a communication medium to transmit artificial data across the body. NC features body-wide communication coverage while it demands zero investment cost on the infrastructure, does not rely on any external energy source, and exposes the body to zero electromagnetic radiation. n addition, unlike many conventional body area networking techniques, NC is able to provide communication among manufactured electronic machines and biologically engineered ones at the same time. We provide a detailed discussion of the theoretical and practical aspects of designing and implementing distinct paradigms of NC. We also discuss NC future perspectives and open challenges.

Adviser: Massimiliano Pierobon