Husker engineer Eric Markvicka is developing a new approach for detecting acute exacerbations of chronic conditions.
With support from the National Institutes of Health, Markvicka is leading a project aimed at developing a wearable monitoring device that contains multiple types of sensors, enabling faster and more accurate detection of exacerbations of chronic obstructive pulmonary disease and chronic conditions like asthma, heart disease and other inflammatory disorders. Eventually, the technology may help everyday people monitor their overall health and attune to early warning signs of illness.
The device will collect multiple streams of physiological data that are time-stamped, enabling the research team to better understand how these functions are linked — and how variations in these couplings might mark a change in health status.
A four-year, $1.2 million grant from the NIH National Center for Complementary and Integrative Health supports the work. Markvicka is collaborating with Stephen Rennard and Ran Dai from the University of Nebraska Medical Center, Kate Cooper from the University of Nebraska at Omaha and Jenna Yentes from Texas A&M University.
Detecting and promptly treating acute exacerbations of COPD and other chronic conditions is an important avenue for reducing complications and mortality.
But in many cases, approaches for detecting flare-ups are flawed and time-consuming. The current gold standard for COPD — patient-reported questionnaires — require patients to frequently report their status, which is burdensome. They also require two to three days to establish a diagnosis, a lag that, in some cases, worsens outcomes.
“The goal is to create a wearable device for these patients that can be used as a medical diagnostic to detect acute exacerbations in a timelier manner: over the timespan of hours, as compared to days,” said Markvicka, Robert F. and Myrna L. Krohn Assistant Professor of Biomedical Engineering. “This framework can be applied to many other chronic conditions that are characterized by acute exacerbations that require timely treatment.”
A major innovation of the team’s device is that it is multimodal, meaning it measures multiple physiological parameters. Many existing wearables, including medical-grade devices, capture a single type of data: pulse or heart rate, for example. By looking at only one data category, these devices fail to provide a holistic view of the wearer’s health. To fill that gap, Markvicka’s device will contain sensors monitoring heart rate, respiratory and gait data to identify changes in whole person health.
It will also integrate data from an “electronic nose” — a passive sensor that monitors chemicals excreted from the skin or breath, which are rich in physiological data. This additional layer of information will enhance the device’s diagnostic capacity and provide an increasingly complete picture of a person’s health.
Another major advantage of the team’s device is that it provides continuous, time-stamped data for each physiological parameter. This differs from most commercially available wearable devices, which collect data over short, intermittent stretches of time: The Apple Watch, for example, records data in 30-second intervals.
Access to uninterrupted, time-registered data will enable Markvicka’s team to explore the potential of biorhythm interconnectivity as an earlier marker of changes in health. Research shows that physiological functions are coupled in reliable ways: In mammals, for example, breathing and gait patterns predictably influence each other in a way that maximizes energy efficiency.
This differs in people with COPD: For them, the two functions are much more tightly coupled, reflecting an inability to dynamically adapt to exertion. Changes in that pairing might serve as an early warning sign of an exacerbation. Markvicka’s team will explore whether changes in biorhythm interconnectivity may better predict changes in health compared to an individual parameter alone.
The device is also physically designed to offer major improvements over currently available medical monitoring devices, some of which are bulky and cumbersome to wear. The device, which would adhesively attach to the wearer’s chest, is soft, low-profile and conforms to the body.
To test efficacy, Markvicka’s team will conduct a clinical study through UNMC that tests the device in 45 people with COPD. In addition to exploring the accuracy of biorhythm couplings in detecting health changes, the researchers will determine whether any of the individual physiological parameters can predict an exacerbation more quickly than standard patient-reported outcome surveys.
Eventually, the technology could enable clinicians to monitor patients remotely, a major benefit to people living in rural areas, which are often far from specialists and major medical centers.
Markvicka also envisions that down the road, everyday users will benefit from multimodal wearables. Right now, smart watches can tell people how many steps they took or estimate the quality of their sleep. But the devices don’t put that information into the context of overall health and environmental factors, such as weather or air quality, that can influence measures like step count.
“One of our big goals is to provide a complementary diagnostic tool that clinicians can use to support their decision-making and improve whole person health. This will be accomplished by using this low-level data, like step count, and combining it with other biological rhythms to provide more high-level insight, like whether a person is getting sick.
“Our human physiology undergoes subtle changes much earlier than clinically recognizable symptoms, providing a window for early intervention.”
The project is funded through the Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science program, an NSF-NIH interagency initiative that supports high-risk, high-reward advances across a range of disciplines to address pressing questions in the biomedical and public health communities.
