2019 ARCHES Projects

FALL 2019

USING SIMULATION TO EVALUATE AND IMPROVE TEAM COGNITION IN HANDOFFS

Collaborators: Abigail Wooldridge, Illinois/Industrial and Enterprise Systems Engineering and Paul Jeziorczak, OSF

This project is the continuation of earlier research. It attempts to better measure the impact of improvements made to the process of handoffs which are important to provide opportunities to detect and correct errors. Recent work has conceptualized handoffs as team cognition, measured using human factor techniques outside of health care. Researchers believe team cognition theory can be applied to improve handoffs with education and technology-based interventions.

LUNG CANCER RADIOMICS AND RADIOGENOMICS

Collaborators: Minh N. Do, Illinois/ Coordinated Science Laboratory and Joseph R. Evans, OSF/UICOMP

In an attempt to reduce the leading cause of cancer deaths in the United States, this project would combine imaging and genomic features to develop a radiogenomics risk signature, offering valuable information about the aggressiveness of the newly diagnosed lung cancer. Furthermore, this project takes advantage of and extends the OSF lung cancer screening program by establishing IRB-approved imaging and pathology repositories.

MIXED-REALITY BASED VISUALIZATION AND SIMULATION OF NERVE CONDUCTION STUDY

Collaborators: Vahid Tohidi, OSF and Pramod Chembrammel, Illinois/Health Care Engineering Systems Center

This proposal attempts to use a mixed-reality technology platform to train medical students, technicians, neurology residents and fellows how to better recognize pathological patterns in results of nerve conduction studies. Researchers believe this type of education will shorten the learning curve for accurate and effective application of NCS data in diagnosis of peripheral nerve disorders which can be debilitating for those impacted.

SURGICAL PLANNING VIA PREOPERATIVE SURGICAL REPAIR OF NEXT-GENERATION 3D, PATIENT-SPECIFIC, CARDIAC MIMIC

Collaborators: Hyunjoon Kong, Illinois/Bioengineering and Mark D. Plunkett, OSF

This project aims to 3D print realistic physical organs and tissues to help surgeons better plan for specific operations and train new surgeons. This team has developed a 3D printing approach, using materials that mimic the softness and toughness of anatomy. This work is expected to advance the field of clinical simulation to the next level.

I-AREA-P: AN INTELLIGENT MOBILITY-BASED AUGMENTED REALITY SIMULATION APPLICATION FOR PEDIATRIC RESUSCITATION TRAINING

Collaborators: Trina Croland, OSF/UICOMP and Abigail Wooldridge, Illinois/Industrial & Enterprise Systems Engineering

Jump Simulation created an augmented reality-based Pediatric Code Cart app that allows medical students and professionals to easily learn about the contents of the cart, how it works, and how to use it in the event of a pediatric emergency. This team will work to expand this platform to include additional adult resuscitation modules as well as procedural skills elements related to pediatric resuscitation.

ROBOTIC ARM NEUROLOGICAL EXAM TRAINING SIMULATOR FOR ABNORMAL MUSCLE TONE

Collaborators: Elizabeth Hsiao-Wecksler, Illinois/Mechanical Science and Engineering and Christopher Zallek, OSF/UICOMP

This group of individuals is expanding work to create multiple robotic arm simulators that mimic abnormal muscle behaviors. These training devices are expected to help medical students, interns, residents, nurses and physical/occupational therapists understand the difference between spasticity and rigidity in patients to correctly diagnose neurological conditions.

PEDIATRIC SEPSIS GUIDANCE SYSTEM

Collaborators: Lui Raymond Sha, Illinois/Computer Science and Richard Pearl, OSF/UICOMP

In an effort to help clinicians diagnose sepsis in pediatric patients sooner, this team is creating a computerized pediatric sepsis best practice guidance system. This software will allow for early detection, diagnosis and treatment of sepsis in children. The goal is to improve patient care and reduce medical errors. It will first be tested in a simulation setting.

MULTI-MODAL SKIN LESION IDENTIFICATION & EDUCATION SIMULATOR: AUGMENTED REALITY INTERACTIVE SKIN LESION APP

Collaborators: Scott Barrows, OSF/Jump and Steve Boppart, Illinois/Bioengineering

This project expands on an augmented reality-based mobile app developed last year to train medical students in the identification, diagnosis and treatment of skin lesions, masses and other abnormalities. The second phase aims to give learners the ability to see beneath the skin to view skin lesions and their pathologies that cannot be seen on the surface.

INTEGRATING SOFT ACTUATORS IN A HEART SIMULATOR TO MIMIC FORCE FEEDBACK IN CARDIAC TRANS-SEPTAL PUNCTURE

Collaborators: Girish Krishnan, Illinois/Industrial Systems Engineering and Abraham Kocheril, OSF

This team is creating a realistic soft heart simulator that allows learners to feel what it’s like to poke and prod cardiac tissues to make crucial operating decisions. While this simulation device targets a specific surgical process for the heart, the idea is to create more soft structures for other surgical procedures.

VIRTUAL HEART PATCH FOR DETERMINING COMPLEX SHAPES FOR SURGICAL PATCHING

Collaborators: Arif Masud, Illinois/Civil and Environmental Engineering and Matthew Bramlet, OSF/UICOMP

This group is developing a software module that allows surgeons to simulate the creation of complexly-shaped 2D heart patches in a virtual reality environment. Surgeons would use this simulation to determine the size and shape of a patch that needs cut from a 2D sheet of flexible cloth-like material that can be used in a real heart patch surgery.

AUTOMATED AND ADAPTIVE WHOLE-BODY SEGMENTATION FOR VISUALIZATION OF ANATOMY, LESIONS, AND INTERVENTION PATHWAYS FOR MEDICAL TRAINING

Collaborators: Brad Sutton, Illinois/Bioengineering and Matthew Bramlet, OSF/UICOMP

This project expands on a previous effort to develop an automated segmentation program to create congenital heart defects in 3D, viewable in a variety of digital formats. The current proposal seeks to develop another automated segmentation platform for the creation of 3D content of the whole body for medical training in virtual reality.