Funded Projects

HCESC Research

In-Home Rehab Care

PI: Kesh Kesavadas, HCESC

In the future, the occupational therapist helping you re-learn how to use a fork following a stroke might be a computer. Researchers at the University of Illinois at Urbana-Champaign and the University of Buffalo are developing technology that could assist stroke victims and others with occupational and physical therapy at home. Led by Professor Kesh Kesavadas, researchers are developing a system based on haptics, the process of recognizing objects through touch. The team is working to create a low-cost model that can help enforce proper technique through exercises, which will be designed using data collected by analyzing the motion of healthy subjects. This research was funded by NSF.

Robotic Surgery and Simulation

PI:  Kesh Kesavadas, HCESC

In the same way that pilots train for actual flights through simulation, the next generation of doctors will train for surgery. A group of researchers from the University of Illinois, led by Industrial and Enterprise Systems Engineering Professor Kesh Kesavadas, and including Dr. David Crawford, is at the forefront of a technology that will make that training virtual. The project will utilize HCESC’s new RAVEN II, Tele-Surgery Robot, which will allow future doctors to conduct hands-on training in robotic surgery without the use of a patient. It is one of the first steps in linking cutting-edge medical research already taking place on campus with the engineering-based College of Medicine, opening in 2018. This research was partially funded by NSF and Jump ARCHES.

Virtual Reality Visualization of Patient Specific Heart Model

PI:  Kesh Kesavadas, HCESC; Matt Bramlet, Jump Trading and Simulation Education Center/OSF; Steve LaValle, Computer Science

Currently, doctors are using 2D tools and images to visualize a child’s 3D heart and make important surgical decisions. Because of the complex intra- and extra-cardiac relationships and connections, this imperfect method makes it difficult for doctors to accurately diagnose a patient. Researchers at the HCESC, Jump Simulation Center, and OSF Health Care are using 3D immersive virtual reality technology to help solve this problem. They have created an intuitive model generated from patient-specific MRIs using stereoscopic 3D head-mounted displays. This project is funded by Jump ARCHES, and is conducted under the direction of Professor Kesh Kesavadas, HCESC, Dr. Matt Bramlet, Jump Trading and Simulation Education Center/OSF, and Professor Steve LaValle (computer science), at the University of Illinois at Urbana-Champaign.


Jump ARCHES Funded Projects

Abnormal Muscle Tone Behavior Diagnostic Device

PI: Elizabeth Hsiao- Wecksler, Mechanical Science and Engineering

Under the direction of Professor Elizabeth Hsiao- Wecksler, (mechanical and science engineering), a large team of clinicians and researchers will create a novel robotic training simulator that will allow healthcare students, residents, and young clinicians to practice feeling and identifying abnormal muscle tone behaviors. These sorts of behaviors are typical in patients with brain lesions; caused by Parkinson’s disease, multiple sclerosis, and stroke. Funded by Jump ARCHES, the team is developing a forearm simulator that will mimic different levels of abnormal muscle behaviors in the elbow. To accommodate the complexity of these muscle behaviors, researchers will advance novel fluid and geometry designs to provide a realistic replication.

Developing MRI Acquisitions and Protocols to Enable Automated Segmentation of Cardiac & Brain Images

PI: Brad Sutton, Bioengineering

In this project, researchers will develop an imaging protocol that will help physicians get a better picture of the heart and brain. Work will focus on providing maximal differentiation of different tissue types in the brain and heart of patients undergoing MRI diagnostics. This will result in several acquisitions that, when combined, provide maximal tissue separation in a multidimensional histogram. Using open-source algorithms, they will develop processing scripts that automatically create segmented and labeled models of the tissue types and states in a 3D structure of the heart.

Development of a Robotic Forearm to Simulate Abnormal Muscle Tone Due to Brain Lesions

PI: Dr. Elizabeth Hsiao-Wecksler, Mechanical Science and Engineering

To aid patients with brain lesions, who often suffer from abnormal muscle tone, Hsiao-Weckler’s team is refining a forearm simulator that can more accurately present different selectable characteristic patterns of spasticity and rigidity in the elbow during flexion, ensuring that the simulated responses are comparable to real patients. The researchers will use biomechanical data from clinician-applied force functions data to update the design parameters of the forearm simulator. The outcomes will be used to inform the development of enhanced simulators for mimicking additional behaviors, device design using fluids and flow channel configurations, and future training mannequins with moveable limbs. This project is a continuation of the proposal funded previously by ARCHES.

Interactive Technology Support for Patient Medication Self-Management

PI: Dan Morrow, Educational Psychology

Researchers are developing a natural language processing tool that translates technical medication information into patient-centered language in electronic medical records (EMR). Morrow’s group is integrating patient-centered language into a conversational agent (CA)-based “medication adviser” system that supports collaboration and emulates best practices gleaned from face-to-face communication techniques. The researchers also will engage patients by developing interactive capabilities, such as using “teachback” when communicating with patients.

Multi-Modal Medical Image Segmentation, Registration & Abnormality Detection for Clinical Applications

PI: Thomas Huang, Electrical and Computer Engineering

Huang will lead a team that develops an automatic 3D segmentation method, making it easier to separate out images of particular organs from an entire 3D rendering. As a result, physicians will be able to better detect abnormalities in medical images.

Multi-Robot Minimally Invasive Single Port Laparoscopic Surgery

PI: Placid Ferreira, Mechanical Science and Engineering

Ferreira is working to develop a new robotic platform that that enables high-fidelity digital simulation, which will facilitate easy surgical training for clinicians. The robot will allow surgeons to translate the dexterity, torque, and triangulation capabilities of the human in-vivo and will offer a high level of configurable and customizable methods for different surgical procedures. In addition, the robot will be portable and easy to use in field and emergency operations, as well as potentially low cost.

Safety and Reliability of Surgical Robots via Simulation

PI:  Ravi Iyer, Electrical and Computer Engineering

In 2015, researchers at Illinois, MIT, and Rush University Medical Center reported that surgical robots had caused 144 deaths in 14 years. Now, computer engineers at Illinois and surgeons at OSF Saint Francis Medical Center in Peoria are collaborating on new research to improve the reliability and safety of minimally invasive robotic surgery. This research, led by Professor Ravi Iyer, (electrical and computer engineering), will create platforms for simulation of realistic safety-hazard scenarios in robotic surgery and develop tools and techniques for the design and evaluation of the next generation of resilient surgical robots. The work will help improve not only the safety of robotic surgical systems, but also simulation-based training of future surgeons.

Simulation Training for Mechanical Circulatory Support using Extra Corporeal Membrane Oxygenation (ECMO) in Adult Patients

PI:  Pramod Chembrammel, University of Illinois at Urbana- Champaign; Matt Bramlet, University of Illinois College of Medicine at Peoria; Jai Raman, Oregon Health and Science University

Dr. Pramod Chembrammel, University of Illinois at Urbana- Champaign, Dr. Matt Bramlet, University of Illinois
College of Medicine at Peoria, and Dr. Jai Raman, Oregon Health and Science University, are developing a simulator to train surgeons in using extra-corporeal membrane oxygenation (ECMO) to provide artificial oxygenation to blood cells. This skill, which is difficult to perfect without practicing on real patients, helps save failing hearts and lungs during a surgery. The researchers are modifying the DR DopplerTM blood flow simulator, which simulates blood flow in the vasculature, to develop a working prototype where the blood flow changes colors based on oxygenation.

Surgical Planning via Preoperative Surgical Repair of Next Generation 3D, Patient Specific, Cardiac Mimic

PI: Rashid Bashir, Electrical and Computer Engineering and Bioengineering

Led by Bashir, this Illinois team is working to improve care for pediatric cardiac patients. Researchers will leverage CT imaging and segmentation approaches to create new models for printing 3D infant hearts that mimic the structure, material properties, and physical defects of tiny patients. Physician will use the 3D models to practice surgical techniques and then use imaging methods to evaluate the effectiveness of the procedure.