Your smartwatch will soon be able to detect signs of heart failure.
Recent research has introduced a method capable of identifying congestive heart failure (CHF) using electrocardiogram (ECG) data from smartwatches, achieving a remarkable accuracy of 90% in patients.
Congestive heart failure (CHF) is a condition that affects more than five million Americans. For individuals over 65, it is the most frequent diagnosis during hospitalizations. According to data from Johns Hopkins Medicine, one in nine deaths lists heart failure as one of the contributing causes. However, advancements are being made that could change this reality, thanks to new developments in wearable technology.
Researchers at the University of Tampere have created an innovative method using smartwatches to detect congestive heart failure. This multidisciplinary project, which involves experts in heart health and machine learning, has resulted in a real-time analysis system that integrates with smartwatches and heart rate monitors.
Heart diseases often exhibit a characteristic pattern of cardiac activity, which experts can analyze to identify signals of severe problems. An example is the detection of atrial fibrillation (AFib), which looks for irregularities in heart rhythm using electrocardiogram (ECG) data. In this new approach, the team applies a similar strategy to diagnose CHF in patients, using information derived from RR intervals, which are representative of the duration of a ventricular cardiac cycle.
The researchers assessed the accuracy of their technique by comparing it with a control group of healthy individuals and those with AFib issues. According to the study published in the journal Heart Rhythm O2, smartwatches can identify signs of congestive heart failure with remarkable accuracy. This system is not only accessible and cost-effective, but it also has the potential to detect severe heart problems in a timely manner and save lives. The authors of the study emphasize that this approach demonstrates the promise of non-invasive and cost-effective analysis of RRI intervals for the early detection of CHF and AFib.
In terms of accuracy, the method achieved a sensitivity of 90% and a specificity of 92% in detecting markers of heart failure and AFib. Last year, the same team developed another methodology that can predict the risk of death from sudden cardiac arrest using just one minute of heart rate measurement on a smartwatch. Professor Jussi Hernesniemi, a cardiologist at Tays Heart Hospital, commented that the findings pave the way for early detection of congestive heart failure using readily available equipment, thus eliminating the need for complex diagnostic procedures.
This latest advancement adds to a series of promising research initiatives in the field of smartwatches. Over the past decade, these devices have evolved from simple digital accessories to powerful health detection tools. Currently, there are smartwatches that measure blood pressure and detect signs of sleep apnea, while blood glucose monitoring is also expected to be implemented soon. Recent studies have also shown how smartwatch data can help accurately detect psychiatric illnesses and trace their genetic roots.
