Current Projects

Jump ARCHES Awards Grants for Fall 2021

Twenty research projects are sharing more than $1,400,000 in funding through the Jump ARCHES research and development program to focus on the following areas:

  • Promoting recovery post-COVID-19 or similar health crises, both from a patient level and broader perspective of public health as well as the social and economic impact on health care.
  • Addressing evolving standards of care to incorporate personalized precision medicine and genomic best practices.
  • Advancing data security and privacy, and serving to increase institutional and patient confidence in sharing sensitive health data.
  • Addressing treatment and the health literacy of historically underserved populations.
  • Reducing the administrative burden at the bedside to increase the quality of patient interactions.
  • Assisting in diagnosis and treatment of neurological disorders through collaborative efforts with the OSF HealthCare Children’s Hospital of Illinois and OSF HealthCare Illinois Neurological Institute.

The Jump ARCHES program is a partnership between OSF HealthCare and The Grainger College of Engineering at the University of Illinois Urbana-Champaign (U of I) and the University of Illinois College of Medicine in Peoria (UICOMP).

The funding supports research involving clinicians, engineers and social scientists to rapidly develop technologies and devices that could revolutionize medical training and health care delivery. A requirement of the grant applications was for solutions that could be deployed quickly, within four to six weeks. Investigators were also encouraged to consider how to best mitigate the impact of age, location, and social barriers in delivering quality health care to vulnerable populations.

Fall 2021 Project Awards

High Trust Patient Outreach

  • Gang Wang, Assistant Professor of Computer Science, University of Illinois Urbana-Champaign, Grainger College of Engineering
  • Jonathan Handler, MD, OSF HealthCare Senior Fellow, Innovation, OSF HealthCare, Clinical Intelligence
  • Nick Heuermann, OSF HealthCare, OSF Innovation
  • Cody Zevnik, OSF HealthCare, OSF Innovation, Performance Improvement

This project aims to survey, design, and potentially prototype feasible solutions to enable secure patient outreach for patients across all levels of socioeconomic status. We also want to provide patients and doctors with a list of best practices to use the solution to communicate securely.

Point-cloud segmentation for daily adaptive prostate therapeutic planning

  • Angela Di Fulvio, Assistant Professor, University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Department of Nuclear, Plasma, and Radiological Engineering
  • Gregory M. Hermann, MD, MPH; University of Illinois College of Medicine at Peoria, Clinical Assistant Professor, OSF HealthCare, Department of Radiation Oncology

We propose to develop and demonstrate deep-learning-based point cloud models for the registration and segmentation of planning target volumes (PTV) and organs at risk, enabling daily adaptive planning of prostate cancer (PCa) radiation therapy.

Improving the Lives of Children with Asthma by Individualizing the Asthma Care Plan Based on Children’s Home Exposure to Asthma Triggers

  • Elise Albers, MBA, MPH; Manager Population Health, Women’s and Children’s Service Line, OSF HealthCare
  • Sotiria Koloutsou-Vakakis; Senior Lecturer and Research Scientist, University of Illinois at Champaign-Urbana, The Grainger College of Engineering, Civil and Environmental Engineering
  • Margarita Guarin, MD; Assistant Professor, University of Illinois College of Medicine at Peoria, Pediatrics, Pulmonology

The project team proposes a pilot study with indoor air monitoring devices (sensors) that can be deployed in homes and schools of a small cohort of OSF pediatric patients with asthma. The air quality data collected by these sensors will be used to individualize the asthma care plan, taking into account the environmental allergens and pollutants that are present in the patient’s home and providing education on how to mitigate these environmental exposures.

Development of a Trusted Execution Enclave to Securely Link Computational Modeling to a Medical Imaging Database

  • Matthew Bramlet, M.D., Department of Pediatrics University of Illinois College of Medicine – Peoria; Advanced Imaging and Modeling Lab, Jump Simulation
  • Brad Sutton, Ph.D., Department of Bioengineering University of Illinois at Urbana-Champaign Grainger College of Engineering
  • Andrew Miller, Ph.D., Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign Grainger College of Engineering

The primary objective of this project is to create a Picture Archiving and Communication System (PACS) plug-in tool that will allow researchers to run various algorithms on these large imaging datasets without exposing protected health information (PHI). This proof of concept project requires solving several problems to bridge the gap between research algorithms and access to an imaging database while ensuring data security and privacy.

Smart phone App for Migraine referral Optimization using MIG-RO (Migraine Referral Optimization)

  • Hrachya Nersesyan MD, PhD, OSF HealthCare, Illinois Neurological Insititute; University of Illinois College of Medicine Peoria
  • Lusine Demirkhanyan PhD, University of Illinois College of Medicine Peoria
  • Yelena Nersesyan MD, PhD, University of Illinois College of Medicine Peoria
  • Christopher Gondi PhD, University of Illinois at Urbana-Champaign; University of Illinois College of Medicine Peoria
  • Inki Kim PhD, University of Illinois at Urbana-Champaign

The goal of this project is to streamline diagnosis of migraine at the patient intake level to reduce patient engagement time and improve appropriate and timely referrals to headache specialists. To address the problem of underdiagnoses we plan to develop a Migraine Referral Optimization (MIG-RO) smartphone application, which can be installed on any smartphone or tablet-like device to enable expedited diagnosis at the patient intake level, recommend first steps in management, and facilitate appropriate referrals to headache specialists.

Digitized Neurological Exams (DNE) with Smartphones/Tablets - A Clinical Recording Pilot Study

  • Minh Do, Professor, University of Illinois at Urbana-Champaign, ECE/CS/BioE
  • Christopher Zallek, MD, OSF HealthCare, Illinois Neurological Institute
  • George Heintz, University of Illinois at Urbana-Champaign, Health Care Engineering Systems Center (HCESC)

DNE has shown the potential as an accessible, easy-to-use and accurate digital solution for in-person and tele-health.

Physiological and anatomical biomarkers for epilepsy antiepileptic drug therapy

  • Hua Li, Ph.D. DABR; Research Associate Professor, Department of Bioengineering, Cancer Center at Illinois, Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign
  • Michael Xu, MD, PhD, FAAN, FAES; Epileptologist, Director of comprehensive epilepsy center, OSF HealthCare Illinois Neurological Institute, Clinical Professor, Department of Neurology, University of Illinois College of Medicine at Peoria
  • Fan Lam, Ph.D.; Assistant Professor, Department of Bioengineering, University of Illinois at Urbana-Champaign
  • Yogatheesan Varatharajah, Ph.D.; Research Assistant Professor, Department of Bioengineering, University of Illinois at Urbana-Champaign

This study aims to develop a comprehensive and robust computational model for the prognosis of AED treatment response. Prognosis models will be developed based on advanced belief function theory (BFT) and deep learning (DL)techniques and utilizing a large cohort of retrospective patient cases. Our preliminary studies havedemonstrated the promising performance of the resulting prognosis models.

Development of a Coordinated and Community-Focused Network of Antibiotic Use and Resistance Data

  • Ellen Moodie, Associate Professor, University of Illinois at Urbana-Champaign, College of Liberal Arts & Sciences, Department of Anthropology
  • Thanh (Helen) Nguyen, Professor, University of Illinois at Urbana-Champaign, Grainger College of Engineering, Civil & Environmental Engineering
  • Rebecca Smith, Associate Professor, University of Illinois at Urbana-Champaign, College of Veterinary Medicine, Department of Pathobiology,
  • Rachel Whitaker, Professor, University of Illinois at Urbana-Champaign, School of Molecular & Cellular Biology, Department of Microbiology
  • Brian Laird, Pharmacy Operations Manager, OSF HealthCare, Heart of Mary Medical Center

In order to understand the human context in which antimicrobial resistance evolves, we need to be able to collect and coordinate data on the relationship of people and health care providers in a diverse community that has been identified as a health care desert. This must include both qualitative data in particular vulnerable communities and aggregated and comprehensive but local across health care providers (metadata on prescription practices and diagnostic results) which is uncoordinated amongst the many organizations working in this community. Therefore, we will also create a data coordination platform for the secure and anonymized sharing of data related to antimicrobial use and resistance within the Champaign County community as an exemplar of dynamics in a multi-cultural agricultural landscape with substantial human mobility.

Healing Health Care Disparities among BIPOC Patients through Virtual Reality Cultural Competency Training

  • Charee M. Thompson, PhD, University of Illinois at Urbana-Champaign, College of Liberal Arts and Sciences, Department of Communication
  • Mardia Bishop, PhD, University of Illinois at Urbana-Champaign, College of Liberal Arts and Sciences, Department of Communication
  • Krishan Kataria, MD, OSF HealthCare, Internal Medicine
  • Chrysafis Vogiatzis, PhD, University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Department of Industrial and Enterprise Systems Engineering

The proposed project is a virtual reality (VR) cultural competency training for health care providers (hereafter “providers”) to reduce health disparities among Black, Indigenous, People of Color (BIPOC) patients. By the end of the training, participants will be able to:
(a) Recognize the health inequities experienced by BIPOC patients
(b) Identify their own implicit biases and utilize strategies for managing them
(c) Communicate with BIPOC patients in a culture-centered manner that demonstrates respect and builds trust.

Hands Down: Empowering Children and Families through CPR Education

  • Paul M Jeziorczak, MD MPH, Clinical Assistant Professor of Pediatric Surgery University of Illinois College of Medicine
  • Inki Kim, PhD, Research Scientist Coordinated Science Lab Health Care Engineering Systems Center, University of Illinois at Urbana-Champaign

The purpose of this grant proposal is to create an educational program in mobile app for the family of children admitted to the Children’s Hospital of Illinois surgical service, which will particularly address a significant gap for the families in desperate need of safe and effective CPR skill acquisition, by incorporating a hand-only augmented reality (AR) simulation module. The proposed smartphone-based AR will integrate novel feedback mechanisms to guide the user to a desired range of chest compression with proper hand placement.

TriWave: Inverse Wave Signal Processing for Non-Invasive, Non-Pharmaceutical Migraine Therapy

  • Christopher Gondi PhD, University of Illinois at Urbana-Champaign; University of Illinois College of Medicine Peoria
  • Hrachya Nersesyan MD, PhD OSF HealthCare, Illinois Neurological Insititute; University of Illinois College of Medicine Peoria
  • Lusine Demirkhanyan PhD, University of Illinois College of Medicine Peoria
  • Yelena Nersesyan MD, PhD, University of Illinois College of Medicine Peoria
  • Inki Kim PhD, University of Illinois at Urbana-Champaign

In this proposal we address the imbalance between excitatory and inhibitory cortical-subcortical neurotransmission using the inverse wave approach to manage migraine-associated pain (see figure). Our approach cancels anomalous EEG wave patterns in migraine patients at the pre-, intra- and post phases of migraine.

A Deep-Learning Augmented Point-Of-Care Device for Antibody Quantification

  • Yang Zhao, Ph.D., Assistant Professor, University of Illinois at Urbana-Champaign The Grainger College of Engineering, Department of Electrical and Computer Engineering.
  • Yun-Sheng Chen, Ph.D., Research Assistant Professor, University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Department of Bioengineering, Carle Illinois College of Medicine
  • John J. Farrell, M.D., Professor of Medicine, University of Illinois College of Medicine, Medical Director OSF HealthCare Microbiology & Infection Control

In this proposal, we will address the unmet need for point-of-care serological tests with quantifiable and improved accuracies. Our goal is to develop a cost-effective SARS-CoV-2 serological testing mechanism that minimizes false-positive rate and is ready for scaling up for large-scale screening. The objective of this proposal is that the team will work together to develop a machine-learning-enabled detection mechanism that can quantify the antibody responses due to SARS-CoV-2 in minutes with pg/mL sensitivity using a cost-effective chiral fluorescent sensor and handheld readout devices.

Low pathogen counts in whole blood samples

  • Rashid Bashir, Ph.D., University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Department of Bioengineering.
  • Enrique Valera, Ph.D., University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Department of Bioengineering
  • John J. Farrell, MD., Professor Clinical Medicine, University of Illinois College of Medicine; Director of Diagnostic Microbiology & Immunology, OSF HealthCare System Lab

This project will demonstrate the feasibility of a new platform to achieve the detection of low bacteria and fungi counts (1-3 CFU/mL), in less than 2 hours, analyzing large volumes of whole blood (up to 5 mL) from clinical samples. Likewise, we would like to advance our understanding of the reaction mechanisms and fundamental questions regarding the bi-phasic reaction.

Virtual reality simulation training for neonatal procedures

  • Nicole Rau, M.D., M.S., University of Illinois College of Medicine at Peoria, Pediatrics, Division of Neonatology
  • M. Jawad Javed, M.D., University of Illinois College of Medicine at Peoria, Pediatrics, Division of Neonatology
  • Harris Nisar, Simulation Engineer, University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Health Care Engineering Systems Center

Through a combined effort between engineers and artists from the University of Illinois at Urbana-Champaign (UIUC) and physicians from the University of Illinois, College of Medicine in Peoria (UICOMP) division of neonatology, we aim to develop an innovative VR platform on which to provide simulation training in neonatal procedures for community providers. This software will be based on a curriculum developed by neonatal experts.

Monitoring the Health of the Hospital: Using Wearable Sensors to Monitor Nursing Stress

  • Abigail R. Wooldridge, PhD; University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Department of Industrial and Enterprise Systems Engineering
  • Deborah McCarter, DNP; Vice President and Chief Nursing Officer, OSF HealthCare Heart of Mary Medical Center
  • Alexandra Chronopoulou, PhD; University of Illinois at Urbana-Champaign, College of Liberal Arts & Sciences, Department of Statistics

Medical errors are estimated to cause more than 250,000 deaths per year in the U.S. and could be by caused human factors/ergonomics (HFE) issues, including provider stress and fatigue. Our long-term goal is to develop a system to monitor provider stress in real time, allowing health care organizations to reduce the risk of burnout and medical error. The overall objectives in this proposal are to develop a scalable data stream of physiological data and validate knowledge extracted from the data stream.

Facial pressure ulcer detection using a wearable sensor patch (WSP)

  • Anusha Muralidharan, Simulation Engineer, University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Health Care Engineering Systems Center
  • Placid M. Ferreira, PhD, Director, Micro-Nano Mechanical Systems Lab, Professor, Department of Mechanical Science and Engineering, Grainger College of Engineering, University of Illinois at Urbana
  • Shandra Jamison, Simulation Manager, Carle Illinois College of Medicine and Jump Simulation Center, University of Illinois at Urbana-Champaign
  • Deborah Mccarter, DNP, RN, Vice President and Chief Nursing Officer OSF Heart of Mary Medical Center

Our proposal seeks to develop a wireless sensor patch system for continuous monitoring of facial pressure ulcers. We will integrate force, temperature and relative humidity sensors into a flexible printed circuit design (FPCB).

Early Detection and Prediction of Facial Expression for Parkinsonism Powered by Few-Shot Learning

  • Yuxiong Wang, Assistant Professor, Ph.D., Department of Computer Science, The Grainger College of Engineering, University of Illinois at Urbana-Champaign
  • Christopher M. Zallek, M.D., Illinois Neurological Institute, OSF HealthCare

Neurological disorders are among the most frequent causes of morbidity and mortality in the US, the most common being Parkinson’s and Alzheimer’s. The insidious and heterogeneous onset of neurodegenerative diseases challenges the abilities of the primary care systems to appropriately diagnose and manage these diseases. We propose an AI supported system that tracks facial expressions of neurological patients and reports findings to the neurologists. In this project we focus on discriminating facial expressions that are associated with Parkinsonism.

Augmented reality assisted endotracheal intubation (ETI) trainer

  • Anusha Muralidharan, Simulation Engineer, Health Care Engineering Systems Center, Grainger College of Engineering, University of Illinois at Urbana-Champaign
  • Praveen Kumar, MD, Professor of Clinical Pediatrics, University of Illinois College of Medicine at Peoria.
  • Thenkurussi Kesavadas, PhD, Director, Health Care Engineering Systems Center, Professor, Grainger College of Engineering, University of Illinois at Urbana Champaign
  • Neil Mehta, MD, Clinical Assistant Professor of Surgery, University of Illinois College of Medicine at Peoria

This proposal aims to develop a high fidelity training simulator to train health professionals, medical students and residents on endotracheal intubation (ETI) and provide feedback through

  1. The design and develop a high fidelity ETI smart trainer to teach endotracheal intubation
  2. Collecting data on health care providers proficient in the procedure of ETI to establish normativedata to create a performance trajectory model
  3. Development of an augmented reality (AR) application for visualization and feedback
  4. Validation of the developed augmented reality based simulation trainer by comparing theperformance of novice and proficient health care providers in the procedure of ETI tounderstand differences in technique between these groups

FlightPath and Neuro DNA: Creating a New Interoperability Standard for the Evaluation of Neuro cognitive Impairment

  • Adam Cross, M.D., FAAP; Assistant Professor of Clinical Pediatrics and Clinical Informatics Specialist, Head of the Children’s Innovation Lab, JUMP Trading Simulation and Education Center; University of Illinois College of Medicine Peoria, Department of Pediatrics
  • Inki Kim, PhD; Research Scientist, Coordinated Science Lab, Health Care Engineering Systems Center, University of Illinois at Urbana-Champaign

Conditions associated with neurocognitive impairment (NCI) often present heterogeneously through various combinations of physical and cognitive impairments, posing a challenge to diagnosis. Common etiologies, such as traumatic brain injury (TBI) and dementia, are not yet routinely identified through objective lab or imaging results but instead rely on a combination of physical and cognitive evaluations as well as symptom reporting. The testing batteries are primarily paper-based, dependent on language and education, suffer from learning bias, and must be administered by a health care professional. This project seeks to address these limitations by developing a new interoperability standard for NCI based on an individual’s ability to track an object within a mixed reality (MR) space and will first test this paradigm as a novel method for the detection and characterization of concussion.

Prospective Observational Study: Identification of Brain Micrometastatic Disease Using Ultra-High Field Magnetic Resonance Imaging

  • Wael Mostafa, MD, PhD, Department of Neurosurgery, University of Illinois at Urbana-Champaign, Carle Illinois College of Medicine
  • Aaron Anderson, PhD, University of Illinois at Urbana-Champaign, Beckman Institute
  • Paul M. Arnold, MD, FACS, Carle Foundation Hospital, Neuroscience Institute
  • Anant Naik, BS, Carle-Illinois College of Medicine
  • Annabelle Shaffer, MS, Carle-Illinois College of Medicine
  • Sinisa Stanic, MD, Carle Foundation Hospital, Carle Cancer Institute
  • Brad Sutton, PhD, University of Illinois at Urbana-Champaign, The Grainger College of Engineering, Department of Electrical and Computer Engineering
  • Charee Thompson, PhD, University of Illinois at Urbana-Champaign, College of Liberal Arts and Sciences, Department of Communication
  • Andrew Tsung, MD, OSF HealthCare, Department of Neurosurgery
  • Vamsi Vasireddy, DO, Carle Foundation Hospital, Carle Cancer Institute
  • Blake Weis, MD, Carle Foundation Hospital, Department of Neuroradiology
  • Tracey Mencio Wszalek, PhD, University of Illinois at Urbana-Champaign, Beckman Institute

The project outlined here will provide new information about the frequency and prognosis of micrometastases. Comparisons will also be drawn regarding treatment efficacy. Additionally, we include rich quality of life data for brain metastases of all sizes. Combined, this data will support the usage of innovative ultra-high-field imaging in clinical practice and better inform clinicians treating metastatic brain disease.