Champaign, ill. – The time when you need the heart to return to your reference rate after exercise can predict a multitude of cardiovascular or metabolic disorders. In a new study, scientists from the University of Illinois Urbana-Champaign used an “intelligent shirt” equipped with an electrocardiogram to follow the cardiac recovery of participants after the exercise and developed a data analysis tool to predict those who have a higher or lower risk of heart disease.
They report their conclusions in the newspaper of the Ieee Journal of Health Ironics.
“The response from the heart to the exercise provides us with an early indicator of health changes, in particular cardiovascular function and mortality,” said Manuel Hernandezteacher biomedical and translational sciences At Carle Illinois College of Medicine who led research with industrial and corporate systems engineering teacher Richard Sowers and graduate student Ayse Dogan.
“In -depth research has shown (one) association between abnormal recovery of heart rate and various cardiovascular diseases, including heart failure, coronary disease, diabetes mellitus, hypertension and sudden heart death,” the researchers wrote. But the measurement of the RRR is traditionally an involved process requiring a cardiologist, a treadmill and other equipment and expensive staff.
The team wanted to develop a more accessible approach to assess and predict cardiovascular risk. If a portable device could capture relevant data as a person who goes through his daily routines, sending this data to a laboratory or a doctor’s office to analyze, he could put an early diagnosis of potential problems available to many other people.
Photo by Fred Zwickky
To achieve this, researchers used an intelligent shirt developed by the Société de Québec Carre Technologies. The shirt provides sensors to capture continuous measures of heart performance, including monitoring electrical activity and heart rate variability. In total, 38 participants aged 20 to 76 walked on a treadmill at speeds and variable slopes while carrying the device. The study was conducted in 2021 in Illinois during the locking of COVID-19.
The team used automatic learning and other techniques to extract the most significant cardiac health signals from data, designing a system to predict those most at risk of cardiovascular disease.
“We have chosen the median value for recovery of the heart rate of 28 beats per minute as a threshold to separate participants into high -risk and low risk groups,” the researchers wrote. They used other statistical measures to cross -check the results.
“We find values consistent with the different traditional classifiers and cross validation approaches,” said Dogan. This means that the algorithm developed for the study has given reasonably precise results despite the small size of the sample, she said.
The study is a first step towards the use of portable devices to help people more easily assess their risk of heart problems, perhaps catching disturbing trends before turning into full-fledged disorders or causing sudden death, said Hernandez.
“We want to use it to provide us with a more important overview of our underlying cardiovascular function,” he said. “And we want to do something clinically usable.”
“We would like to have a lot of laptop data, then this data is transmitted to a doctor’s office, and the doctor can interpret it,” said Sowers. This would be particularly useful for those who live in rural communities or in other areas with poor access to advanced medical facilities.
Future studies on the use of portable technology to predict cardiovascular risk should increase the number of people studied, follow participants over time and compare their heart activity during exercise and rest, researchers said. Other studies should also focus on integrating technology into standard health practices.
Hernandez is also a subsidiary of the Beckman Institute for Advanced Science and Technologythe departments of bio-engineering And Health and Kinesiologyand Center for social and behavioral sciences in the United States of I. Sowers is also a professor of mathematics and in the National Center for SuperCalculation Applications to Illinois.
Publisher’s note::
To reach Manuel Hernandez, email mhernand@illinois.edu
To reach Richard Sowers, email r–wers@illinois.edu
To reach Ayse Dogan, email Adogan2@illinois.edu
The document “continuous monitoring of the recovery of the heart rate with the ECG signals of portable devices: identify risk groups in the general population” is available online.