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KOÇ UNIVERSITY

GRADUATE SCHOOL OF SCIENCES & ENGINEERING

ELECTRICAL and ELECTRONICS ENGINEERING

MS THESIS DEFENSE BY MELTEM CİVAŞ

 

Title: ICT-based Understanding of Spinal Cord Networks with Applications to Spinal Cord Injuries

 

Speaker: Meltem Civaş

 

Time: September 10, 2018, 13.30

 

Place: ENG B29

Koç University

Rumeli Feneri Yolu

Sariyer, Istanbul

 

Thesis Committee Members:

Prof. Özgür B. Akan (Advisor, Koç University)

Prof. Fatih Alagöz (Boğaziçi University)

Prof. Alper T.  Erdoğan (Koç University)

 

Abstract:

Research efforts in nanotechnology have opened the way for the deployment of nanonetworks comprising nanomachines with bio-inspired capabilities inside the body. Deploying nanonetworks and connecting them to the Internet based on Internet of Bio-Nano Things (IoBNT) framework can result in wide range of possible biomedical applications including treatments techniques of nervous diseases. Molecular communication (MC) has been proposed as a communication technology solution to be employed among nanomachines. Since biological systems use most advanced forms of MC, this motivates information and communication technology (ICT) community to develop bio-inspired communication systems at the nanoscale for nervous system diseases such as spinal cord injuries (SCI), which cannot be recovered to the date by any treatment method. In this respect, a framework was proposed for developing ICT-based treatment and diagnosis tools for nervous disease. According to this framework, understanding of nervous nanonetworks and extracting ICT metrics based on their analysis are the key steps for the development of these techniques. Hence, this thesis focuses on the realistic modeling and information theoretical analysis of spinal cord networks. To this end, we apply existing neuro-spike communication channel models to the particular spinal cord networks to analyze the rate of information flow across them. Based on our analysis, we obtain correlations between several types of spinal injuries and information theoretical metrics. Moreover, we further propose novel ICT-based treatment techniques which can use the advantages aspects of existing and bio-inspired communication & networking methods to recover disrupted communications in the nervous nanonetwork after SCI.

 

 

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