The duration required for the heart to revert to its normal pace following physical activity can indicate various cardiovascular or metabolic conditions. In a recent investigation, researchers from the University of Illinois Urbana-Champaign utilized a "smart shirt," which includes an integrated electrocardiogram, to monitor individuals’ post-exercise heart rate recovery. They then created an analytical instrument designed to assess this information and identify people who might have either elevated or reduced chances of experiencing cardiac issues.
They report their findings in the IEEE Journal of Healthcare Information Technology .
"The reaction of the heart during physical activity gives us an initial sign of shifts in overall health, particularly concerning cardiovascular performance and lifespan,” stated Manuel Hernandez, a professor of biomedical and translational sciences at the Carle Illinois College of Medicine. He conducted this research alongside Richard Sowers, an industrial and enterprise systems engineering professor, as well as graduate student Ayse Dogan.
The researchers noted that extensive studies have demonstrated a link between irregular heart rate recovery and several cardiovascular conditions such as heart failure, coronary artery disease, diabetes mellitus, high blood pressure, and sudden cardiac arrest. However, assessing HRR typically involves complex procedures necessitating the presence of a cardiologist, use of a treadmill, and expensive tools and staff.
The team aimed to create a more user-friendly method for evaluating and forecasting cardiovascular risks. By collecting pertinent information via a wearable device during regular activities, and then transmitting this data for examination at a lab or physician’s clinic, early detection of possible issues could become accessible to a much broader population.
For their research, the scientists utilized an intelligent shirt created by Quebec’s Carre Technologies. This garment features sensors designed to continuously monitor cardiac function, such as measuring electrical activity and heart rate variability. A group of 38 individuals aged between 20 and 76 were recruited for the experiment; they exercised on a treadmill set at different speeds and gradients while equipped with the device. The investigation took place in 2021 in Illinois amid the coronavirus quarantine period.
The team employed machine learning along with various methods to identify the most significant indicators of heart health within the dataset, developing a system aimed at forecasting individuals who have the greatest likelihood of experiencing cardiovascular issues.
"The researchers set the cutoff for heart rate recovery at 28 beats per minute, using this point to divide participants into high-risk and low-risk categories," they noted. Additional statistical analyses were performed to validate these results.
Dogan mentioned that they consistently obtained reliable outcomes using various conventional classifiers and cross-validation methods. This indicates that the algorithm created for their research produced fairly precise findings even though the dataset was limited in size, as she explained.
This research marks an initial move towards leveraging wearable technology to enable individuals to better evaluate their likelihood of experiencing cardiovascular issues. It could potentially identify concerning patterns before they evolve into complete diseases or result in unexpected fatalities, as stated by Hernandez.
He stated, 'Our aim is to gain deeper insights into our fundamental cardiovascular functions through this tool. Additionally, we intend to develop something that can be effectively utilized in clinical settings.'
"Sowers mentioned that ideally, one should gather copious amounts of data from wearable devices, which could subsequently be sent to a healthcare provider. The professional could then analyze this information." Such capability would particularly benefit individuals residing in remote regions or places lacking easy access to sophisticated medical centers.
The researchers suggested that future investigations into using wearable tech for predicting cardiovascular risks should expand the participant pool, track subjects longitudinally, and examine variations in cardiac behavior between physical activity and resting states. Additionally, these studies ought to aim at incorporating this technology seamlessly into routine medical procedures.
More information: Ayse Dogan and colleagues explored continuous heart rate recovery monitoring using ECG signals from wearable devices to identify risk groups within the general population. IEEE Journal of Biomedical and Health Informatics (2025). DOI: 10.1109/JBHI.2025.3550092
Supplied by the University of Illinois at Urbana-Champaign
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