Smart Growing Rod Device for the Treatment of Early Onset Scoliosis

Early Onset Scoliosis (EOS) occurs in children under 10 years of age and many cases have a higher probability of progression during growth. The EOS has been treated with “growing rod” procedure to avoid interference with spinal growth. Patients have to undergo a series of operations to have the rod lengthened for maintaining the correction without affecting the growth of the spine. Adjusting the rods requiring major surgery, costly, and is associated with negative psychosocial outcomes. In an attempt to solve these problems, we have developed a new smart medical device namely, Smart Growing Rod Device (SGRD), that proposes treating EOS with less invasive procedures to minimize the complications associated with the current techniques as well as reducing cost and improving treatment control. This innovative device will have an internal control system, allowing the growing rod to be adjusted based on neural network estimated monthly growth value and a pressure sensor, which determines when the optimum length has been reached. This is accomplished without X rays or other scanning.This study investigates the proposed SGRD for the treatment of EOS via testing our prototype smart growing device with scoliosis model and also with a spine finite element model. The results of those models are very promising and demonstrate system function and effectiveness for treatment of EOS. This will improve quality of life for scoliosis patients, and is more cost-effective than is the traditional growing rod procedure.

Name thesis:degree_name

Doctor of Philosophy (Ph.D.)

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Electrical Engineering

Grantor dc:publisher

University of Dayton

Year dc:date

2013

Author dc:creator

• Abolaeha, Osama Abohamiara

Contributors dc:contributor

• Weber, John

• Electrical Engineering
• Biomedical Engineering
• Biomechanics
• intelligent control systems
• Early Onset Scoliosis
• trajectory generation algorithm
• finite element method

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=dayton1364067419

OAI identifier oai:identifier

oai:etd.ohiolink.edu:dayton1364067419