RESOURCES

PUBLICATIONS

TRUSTED BY TOP INSTITUTIONS, PHYSICIANS, NURSES, & RESEARCHERS

Your research resource

Moberg Analytics is authoring ground-breaking research and publications with some of the top neurocritical care physicians, nurses, and researchers. They have selected us as their partner and are adopting our analytics platform as their tool of choice.

The future of neuromonitoring: The Moberg AI Ecosystem

2024

arXiv Preprint
October 2024

Predicting the Trajectory of Intracranial Pressure in Patients with Traumatic Brain Injury: Evaluation of a Foundation Model for Time Series

Florian D. van Leeuwen, Shubhayu Bhattacharyay, Alex Carriero, Ethan Jacob Moyer, Richard Moberg

Patients with traumatic brain injury (TBI) often experience pathological increases in intracranial pressure (ICP), leading to intracranial hypertension (tIH), a common and serious complication. Early warning of an impending rise in ICP could potentially improve patient outcomes by enabling preemptive clinical intervention. However, the limited availability of patient data poses a challenge in developing reliable prediction models. In this study, we aim to determine whether foundation models, which leverage transfer learning, may offer a promising solution.

Military Medicine
August 2024

Using Physiological Biomarkers to Optimize Management of TBI in Austere Environments

Dick Moberg, Ethan Moyer, Alec Gomba, Meghan Willner, Sean Keenan, Dennis Jarema.

Introduction: Multimodal monitoring is the use of data from multiple physiological sensors combined in a way to provide individualized patient management. It is becoming commonplace in the civilian care of traumatic brain-injured patients. We hypothesized we could bring the technology to the battlefield using a noninvasive sensor suite and an artificial intelligence-based patient management guidance system.

Methods: Working with military medical personnel, we gathered requirements for a hand-held system that would adapt to the rapidly evolving field of neurocritical care. To select the optimal sensors, we developed a method to evaluate both the value of the sensor’s measurement in managing brain injury and the burden to deploy that sensor in the battlefield. We called this the Value-Burden Analysis which resulted in a score weighted by the Role of Care. The Value was assessed using 7 criteria, 1 of which was the clinical value as assessed by a consensus of clinicians. The Burden was assessed using 16 factors such as size, weight, and ease of use. We evaluated and scored 17 sensors to test the assessment methodology. In addition, we developed a design for the guidance system, built a prototype, and tested the feasibility.

Results: The resulting architecture of the system was modular, requiring the development of an interoperable description of each component including sensors, guideline steps, medications, analytics, resources, and the context of care. A Knowledge Base was created to describe the interactions of the modules. A prototype test set-up demonstrated the feasibility of the system in that simulated physiological inputs would mimic the guidance provided by the current Clinical Practice Guidelines for Traumatic Brain Injury in Prolonged Care (CPG ID:63). The Value-Burden analysis yielded a ranking of sensors as well as sensor metadata useful in the Knowledge Base.

Conclusion: We developed a design and tested the feasibility of a system that would allow the use of physiological biomarkers as a management tool in forward care. A key feature is the modular design that allows the system to adapt to changes in sensors, resources, and context as well as to updates in guidelines as they are developed. Continued work consists of further validation of the concept with simulated scenarios.

Physiological Measurement Journal
May 2024

Pitfalls and Possibilities of Using Root SedLine for Continuous Assessment of EEG Waveform-Based Metrics in Intensive Care Research

Stefan Yu Bögli, Marina Sandra Cherchi, Ihsane Olakorede, Andrea Lavinio, Erta Beqiri, Ethan Moyer, Dick Moberg, Peter Smielewski.

The Root SedLine device is utilized for continuous electroencephalography (cEEG)-based sedation monitoring in intensive care patients. cEEG traces can be collected for further processing and calculating additional metrics. However, depending on the device settings during acquisition, the traces may be affected by max/min value cropping or high digitization errors. Our goal was to systematically evaluate the impact of these distortions on the metrics used in clinical research within the field of neuromonitoring.

Special Operations Medical Association (SOMA) Annual Meeting
May 2024

The Development of a TBI Navigator to Augment Management of Brain Injured Patients in Austere Environments

Moberg, R., Flesher, K., Keenan, S., Jarema, D., Moyer, E.J.

Future wars are expected to increase traumatic brain injuries (TBI), overwhelming battlefield medics. To help, we developed a TBI Navigator app, using guidelines from sources like the Brain Trauma Foundation and MACE2/MACE-T. This app creates a comprehensive medical record on a mobile phone, transforming guidelines into assessments and management steps. It triggers management recommendations based on patient conditions and is designed for use in resource-limited environments. Interoperable data structures and common terminology allow easy integration of new modules and devices. This app supports the 2023 DoD Data, Analytics, and AI Adoption Strategy, paving the way for commercialization.

The Development of a TBI Navigator to Augment Management of Brain Injured Patients in Austere Environments
Click to enlarge

International Initiative for Traumatic Brain Injury Research (InTBIR) General Assembly January 2024

Advancing InTBIR's Goals: A Platform for Large-Scale Physiological Data Analytics

Moyer, E.J., Maddux, C., Foreman, B., Rosenthal, E., Diaz-Arrastia, R., Moberg, R.

The International Initiative for Traumatic Brain Injury Research (InTBIR) highlights the need for improved ICU monitoring technology for TBI management. To address this, we developed the Moberg Cloud Platform, a cloud-based system for uploading, reviewing, annotating, analyzing, and exporting high-resolution neurophysiology data from the neuro ICU. This platform is used in the BOOST3 trial and other TBI studies, including TRACK-TBI, in collaboration with Dr. Brandon Foreman at the University of Cincinnati. It was presented to the TRACK-TBI ICU working group in December 2023 and is being evaluated for the Curing Coma Campaign’s Coma Quality Improvement Program. Our platform’s features support InTBIR’s goals by providing centralized access to high-resolution TBI datasets. Future plans include implementing third-party algorithms, integrating with external databases like FITBIR, and validating real-time use in neuro ICUs. We are also developing a reimbursement strategy for multimodal neuromonitoring.

Advancing InTBIR's Goals: A Platform for Large-Scale Physiological Data Analysis
Click to enlarge
The future of neuromonitoring: The Moberg AI Ecosystem

2023

Neurocritical Care Society (NCS) Annual Meeting
August 2023

Towards the Management of Ground Truth Consensus-Based Knowledge in Neurocritical Care

Ethan Jacob Moyer, Xiao Fang, Michael Alec Gomba, Craig Maddux, Dick Moberg.

When information is isolated across literature publications, it can be difficult to see how it all fits together. This is especially true in neurocritical care. Through previous work, our group has extensively reviewed concepts related to harmonization. After exploring many concepts like ontology maps, reference dictionaries, etc., we have determined that a knowledge base is the optimal solution for this problem. This publication serves as preliminary work in an attempt to store, elate, and connect ground truth knowledge in the field that drives the harmonization of concepts, ideas, and data. We aim to extend this work by incorporating this knowledge into CONNECT.

Towards the Management of Ground Truth Consensus-Based Knowledge in Neurocritical Care
Click to enlarge

Integration of High-Resolution Multimodal Neuromonitoring Data and Hospital EMR for Automated Near Real-Time Patient Care Reports

Craig Maddux, Matthew Kirschen, Alexis Topjian, Ryan Burnett, Ethan Jacob Moyer, Hiep Nguyen, Justin Moore, Zujun Yang, Dick Moberg.

In a close collaboration with the Children’s Hospital of Philadelphia (CHOP), we have successfully been able to deliver neuromonitoring reports for pediatric patients at routine intervals. These reports combine artifact-reduced neurophysiology (ICP, ABP, HR, rSO2, etc.), computer trends (PRx, CPPopt, COx, MAPopt), continuous and non-continuous medication administration, summary metrics, clinical impressions, and a technical summary into a one- to two-page report. The report has been designed with the help of Dr. Matthew Kirschen. Our aim is to continue to deploy and validate this technology across hospitals all over the country.

Integration of High-Resolution Multimodal Neuromonitoring Data and Hospital EMR for Automated Near Real-Time Patient Care Reports
Click to enlarge

Methodology of Measuring the Precise Temporal-Spatial Behavior of Electrographic Seizures in Full Term Newborns with Arterio-Ischemic Strokes

France Fung, Ethan Jacob Moyer, Gabriella Grym, Arastoo Vossough, Courtney J. Wusthoff, Renée A. Shellhaas, Stephanie Rau, Swetapadma Patnaik, Dick Moberg, Robert R. Clancy.

Seizures following arterio-ischemic stroke in neonates are focal in nature but may spread to other areas of the brain, making them ideal to study the dynamics of seizure evolution in terms of duration and location. We developed a novel, reduced EEG montage and tested it against a cohort of 29 neonates to quantify the spatial and temporal behavior of electrographic seizures.

Methodology of Measuring the Precise Temporal-Spatial Behavior of Electrographic Seizures in Full Term Newborns with Arterio-Ischemic Strokes
Click to enlarge

Special Operations Medical Association (SOMA) Assembly
May 2023

Assessing the Clinical Value and Deployability of TBI Monitoring Technology for Prolonged Casualty Care

Michael Alec Gomba, Ethan Jacob Moyer, Gabriella Grym, Zack Goldblum, Sean Keenan, Dennis Jarema, Meghan Willner, Victoria Gruen, Kaleigh Kenny, Dick Moberg.

The content of a medic’s pack is incredibly important. If they want to add something in, they likely have to take something out. This is increasingly important in prolonged care scenarios where resources may be limited. Our poster highlights a method we developed in-house for evaluating devices and technology in terms of which are most optimal to use in these environments. Our method crosses the deployability burden of a device – how difficult it is to use in a certain environment – with the value of the measurement(s) it records. By crossing these two scores for over a dozen non-invasive sensors and devices, we were able to rank them in terms of how optimal they are for battlefield use.

Assessing the Clinical Value and Deployability of TBI Monitoring Technology for Prolonged Casualty Care
Click to enlarge
The future of neuromonitoring: The Moberg AI Ecosystem

2022

Neurocritical Care Society (NCS) Annual Meeting
October 2022

Data Anonymization for Cloud-Based Storage of an Extensible Archive Format in Neurocritical Care

Ethan Jacob Moyer, Quoc Thinh Vo, Edilberto Amorim, Craig Maddux, Dick Moberg.

High-resolution data in neurocritical care is enormous, especially for patients that are monitored for days to weeks at a time. This type of data is ideal for machine learning applications, but certain barriers have traditionally thwarted this type of work. Data acquired from medical devices are often stored in proprietary company formats, making it difficult to use for research. Additionally, this data often contains PHI and cannot be moved outside of the hospital without an intermediate anonymization step. Our work highlights a solution to both of these problems. With the help of Dr. Eddy Amorim at the Zuckerberg San Francisco General Hospital, we successfully deployed software to anonymize and convert data from the Moberg CNS Monitor with the aim to use the hospital’s dataset for research.

Data Anonymization for Cloud-Based Storage of an Extensible Archive Format in Neurocritical Care
Click to enlarge

A Taxonomy for Defining Derived Metrics in Neurocritical Care for Machine Learning

Victoria Gruen, Kayleigh Kenny, Meghan Willner, Craig Maddux, Brandon Foreman, Eric Rosenthal, Daiwai Olson, Dick Moberg, Ethan Jacob Moyer.

Reproducibility is a huge problem across all disciplines of science. As the analyses and algorithms become more complex in neurocritical care, it will be more and more difficult for researchers to standardize their algorithms and effectively communicate them to others. We have a unique opportunity to solve this issue early on before it gets out of hand. This poster highlights preliminary work on a method for standardizing analytics using a pallet of interoperable, modular, and simple functions (standard math operations or reference to a publication describing an algorithm). Each metric produced by this method is computed with a metadata string that describes how the metric was derived.

A Taxonomy for Defining Derived Metrics in Neurocritical Care
Click to enlarge

A Gap Analysis of Common Data Elements for Machine Learning in Neurocritical Care

Kayleigh Kenny, Victoria Gruen, Meghan Willner, Craig Maddux, Ethan Jacob Moyer, Brandon Foreman, Eric Rosenthal, DaiWai Olson, Dick Moberg.

A Gap Analysis of Common Data Element for Machine Learning in Neurocritical Care
Click to enlarge

Decision Support in Neurocritical Care Driven by Real-Time Physiology

Meghan Willner, Kayleigh Kenny, Victoria Gruen, Ethan Jacob Moyer, Craig Maddux, Brandon Foreman, Eric Rosenthal, DaiWai Olson, Dick Moberg.

Decision Support in Neurocritical Care Driven by Real-Time Physiology
Click to enlarge

International NeuroTrauma Society (INTS) Annual Meeting
July 2022

CONNECT: A Platform for High-Resolution Multimodal Data Management for Clinical Trials of Brain Injured Patients

Ethan Jacob Moyer, Craig Maddux, Eric Rosenthal, Brandon Foreman, Jonathan Elmer, Karen Hirsch, Dick Moberg.

Live presentation

Neurocritical Care Journal
June 2022

Harmonization of Physiological Data in Neurocritical Care: Challenges and a Path Forward

Richard Moberg, Ethan Jacob Moyer, DaiWai Olson, Eric Rosenthal, Brandon Foreman.

Precision Care in Cardiac Arrest ICECAP (PRECICECAP) Study Protocol and Informatics Approach

Jonathan Elmer, Zihuai He, Teresa May, Elizabeth Osborn, Richard Moberg, Stephanie Kemp, Jesse Stover, Ethan Jacob Moyer, Romergryko G. Geocadin, Karen G. Hirsch, PRECICECAP Study Team.

Neurocritical Care Performance Measures Derived from Electronic Health Record Data are Feasible and Reveal Site-Specific Variation: A CHoRUS Pilot Project

Sophie E. Ack, Shamelia Y. Loiseau, Guneeti Sharma, Joshua N. Goldstein, India A. Lissak, Sarah M. Duffy, Edilberto Amorim, Paul Vespa, Joseph Randall Moorman, Xiao Hu, Gilles Clermont, Soojin Park, Rishikesan Kamaleswaran, Brandon Foreman, Eric S. Rosenthal.

National Neurotrauma Society (NNS) Annual Meeting
June 2022

A Novel Annotation Tool Using Multimodality Neuromonitoring Data Superimposed with Clinically-Relevant Events for Machine Learning

Ethan Jacob Moyer, Dick Moberg, Craig Maddux, Eric Rosenthal, Brandon Foreman, DaiWai Olson.

A Novel Annotation Tool Using Multimodality Neuromonitoring Data Superimposed with Clinically-Relevant Events for Machine Learning
Click to enlarge

Pediatric Academic Societies (PAS) Annual Meeting
April 2022

Semi-Automatic Pediatric Multimodal Neuromonitoring Reports

Ethan Jacob Moyer, Ethan Kuoch, Brandon Foreman, Brain Appavu, Dick Moberg.

Semi-Automatic Pediatric Multimodal Neuromonitoring Reports
Click to enlarge

Society for Critical Care Medicine (SCCM) Annual Meeting
January 2022

Enhancing the Interoperability and AI Readiness of Neurocritical Care Data

Ethan Jacob Moyer, Steven Lawrence, Isamu Isozaki, Jesse Stover, Daniel Habboush, Craig Maddux, Brandon Foreman, Eric S. Rosenthal, Dick Moberg.

The future of neuromonitoring: The Moberg AI Ecosystem

2021

IEEE Signal Processing in Medicine and Biology Symposium
December 2021

A Multimodal Monitoring Approach to Predicting Onset of Physiological Incidents Using Machine Learning

Ethan Jacob Moyer, Isamu Isozaki, Dick Moberg.

A Multimodal Monitoring Approach to Predicting the Onset of Physiological Incidents Using Machine Learning
Click to enlarge

Neurocritical Care Society (NCS) Annual Meeting
October 2021

Using Contextual Data to Enhance Machine Learning in Traumatic Brain Injury

Zack Goldblum, DaiWai Olson, Eric S. Rosenthal, Brandon Foreman, Dick Moberg.

Using Contextual Data to Enhance Machine Learning in Traumatic Brain Injury: Progress from the MIND Workgroup
Click to enlarge

Development and Validation of an Open-Source Optimum Cerebral Perfusion Pressure Tool to Guide Precision Care in every Traumatic Brain Injury

Brandon Foreman, Fei L., Eric S. Rosenthal, Craig Maddox, Daniel Habboush, Zack Goldblum, Dick Moberg.

Live presentation

A Robust Data Archive Format for Traumatic Brain Injury Physiology and Machine Learning

Daniel Habboush, Eric S. Rosenthal, Brandon Foreman, Zack Goldblum, Peter Smielewski, Dick Moberg.

A Robust Data Archive Format for Traumatic Brain Injury Physiology and Machine Learning: Progress from the MIND Workgroup
Click to enlarge

The Accuracy of Coma Prediction Improves During the First 3 Days of Neurocritical Care and is Influenced by Severity and Persistence of Neurologic Deterioration: Results from the CHoRUS Workgroup

Guneeti Sharma, Nooney S., Sophia Ack, India A. Lissak, Craig Maddux, Dick Moberg, Xiao Hu, Hemphill JC, Izzy S., Eddy Amorim, Brandon Foreman, Eric S. Rosenthal.

Live presentation

Extracting Meaning from Neurocritical Care Annotations Requires a Brain Injury-Specific Natural Language Processing Vocabulary: Progress from the MIND Workgroup

Guneeti Sharma, DaiWai M. Olson, Sophie Ack, India A. Lissak, Craig Maddux, Edilberto Amorim, J. Randall Moorman, Xiao Hu, Gilles Clermont, Dick Moberg, Brandon Foreman, Eric S. Rosenthal.

Live presentation

Military Health Science Research Symposium (MHSRS)
August 2021

A Cloud-Based Platform for Data Management in Traumatic Brain Injury Clinical Trials (CONNECT): Progress from the MIND Workgroup

Jesse Stover, Craig Maddux, Eric S. Rosenthal, Brandon Foreman, Anna Rodriguez, Dick Moberg.

A Cloud-Based Platform for Data Management in Traumatic Brain Injury Clinical Trials (CONNECT): Progress from the MIND Workgroup
Click to enlarge

A Robust Data Archive Format for Traumatic Brain Injury Physiology and Machine Learning: Progress from the MIND Workgroup

Daniel Habboush, Eric S. Rosenthal, Brandon Foreman, Zack Goldblum, Peter Smielewski, Dick Moberg.

A Robust Data Archive Format for Traumatic Brain Injury Physiology and Machine Learning: Progress from the MIND Workgroup
Click to enlarge

The Severity and Persistence of Neurological Deterioration are Associated with Clinical Outcome: Progress from the MIND Workgroup

Guneeti Sharma, Nooney S., Ack S., India A. Lissak, Craig Maddux, Dick Moberg, Xiao Hu, Hemphill JC, Izzy S., Eddy Amorim, Brandon Foreman, Eric S. Rosenthal.

Live presentation

Development and Validation of an Open-Source, Online Optimum Cerebral Perfusion Pressure Tool to Guide Precision Care in Severe Traumatic Brain Injury: Progress for the MIND Workgroup

Brandon Foreman, Fei Li, Eric S. Rosenthal, Craig Maddox, Daniel Habboush, Zack Goldblum, Dick Moberg.

Live presentation

Using Contextual Data to Enhance Machine Learning in Traumatic Brain Injury: Progress from the MIND Workgroup

Zack Goldblum, DaiWai Olson, Eric S. Rosenthal, Brandon Foreman, Dick Moberg.

Using Contextual Data to Enhance Machine Learning in Traumatic Brain Injury: Progress from the MIND Workgroup
Click to enlarge

International Neuroscience Nursing Research Symposium
August 2021

MIND Collaborative Effort to Developing Meaning from Annotated Data During Continuous Multimodal Monitoring

DaiWai Olson, Guneeti Sharma, Dick Moberg, Daniel Habboush, Zack Goldblum, Ethan Jacob Moyer, Craig Maddux, Brandon Foreman, Jesse Stover, Eric S. Rosenthal.

Live presentation

Current Neurology and Neuroscience Reports
February 2021

Challenges and Opportunities in Multimodal Monitoring and Data Analytics in Traumatic Brain Injury

Brandon Foreman, India A. Lissak, Neha Kamireddi, Dick Moberg, Eric S. Rosenthal.