SUBJECT: Ph.D. Proposal Presentation
   
BY: Melih Turkseven
   
TIME: Tuesday, November 25, 2014, 3:00 p.m.
   
PLACE: Love Building, 109
   
TITLE: Modeling and Control of a Pneumatically Driven Haptic Interface for Rehabilitation in MRI
   
COMMITTEE: Dr. Jun Ueda, Chair (ME)
Dr. Michael J. Leamy (ME)
Dr. Nader Sadegh (ME)
Dr. Ayanna MacCalla Howard (ECE)
Dr. Fumin Zhang (ECE)
 

SUMMARY

Stroke related brain damage is one of the leading causes of disabilities and death in the US with a growing risk as the average age of the population increases. Brain functions are gradually recovered after a long period of repetitive physical therapies that are provided by healthcare professionals and best monitored by the functional magnetic resonance imaging (fMRI) technology. Rehabilitation therapies have recently started to be automated by the use of robotic devices. Robots are excellent tools for providing quantitative feedback and precision which are very important for the efficiency of the rehabilitation; however, MRI compatibility requirements restrict the use of existing rehabilitation robots. Conventional actuation systems distort the MRI scans and pose a threat on the safety of the patient being monitored due to the intense magnetic field in the MRI environment. By developing MRI-compatible haptic interfaces, robotic rehabilitation under the guidance of fMRI monitoring can be realized.

Previous work designed a pneumatically driven, tele-operated haptic interface and an optical force sensor that satisfy the MRI compatibility requirements. Challenges in the tele-operation of the pneumatic actuators were identified. In order to characterize the system accurately, an appropriate system model and a pressure observer were designed and experimentally validated. The developed system model and pressure observer will be utilized to control the impedance of the interface. The performance of the interface will be tested in a real MRI environment. An MRI compatible system with a controlled impedance could enable a high-resolution observation on the brain activity while the physical therapy is applied with precision. The efficiency of existing rehabilitation routines could be investigated by the use of such robotic devices, which could improve the quality of the healthcare services for the post-stroke patients.