Innovations in Stress ECG Technology and Equipment
The human heart can compensate for various disruptions in its functioning for a relatively long time, which is why many serious diseases in their initial stages are asymptomatic. Of course, precise diagnostic methods help doctors detect diseases in time. Among the many different examinations, the so-called stress ECG tests stand out. All types of stress tests are based on one principle — examining the heart during physical activity. Most cardiological diagnostics are conducted at rest, but this often doesn’t provide a complete picture of organ malfunctions. The advantage of a stress test is that it helps identify various abnormalities at a stage when the heart doesn’t show failures at rest.
Moreover, such examinations help understand how well a person tolerates various physical loads. Therefore, stress tests are a mandatory part of preventive examinations for people whose professions are associated with increased risk (firefighters, pilots, drivers, and others). Cardiological stress tests also help athletes correctly calculate permissible loads and conduct training more effectively.
ECG stress test and Artificial Intelligence
One of the advanced methods for improving stress test results today is using systems with elements of artificial intelligence. Technology based on artificial intelligence allows reducing ECG data processing time, improving the quality of diagnostics, reducing mortality from cardiovascular diseases, and decreasing the workload on doctors. For example, scientists from Stanford University and the University of California, San Francisco have presented a deep neural network for automatic detection and classification of arrhythmia. The AI is capable of recognizing 12 classes of rhythms even for raw electrocardiography data. The training was conducted using 91,232 single-lead ECGs from 53,549 patients. The algorithm can predict rhythm changes approximately once per second. The test set included 328 unique electrocardiograms that were described by cardiologists. The sensitivity and specificity of the algorithms were greater than 90% in almost all cases. The researchers evaluated how accurately the developed AI determines rhythm disturbances from ECG. The F1 score – the harmonic mean of precision and recall of classification – was used for evaluation. The average F1 score for the neural network was 0.837, which is regarded as an outstanding result.
Mobile Solutions
Another prominent innovation is the use of wireless mobile testing systems. They represent a unique solution for ECG recording during stress testing. It doesn’t matter where the testing is conducted — in the laboratory or on-site. The wireless ECG system allows you to stay connected with your patient anywhere.
Superior signal quality
The wireless ECG system allows you to monitor your patient’s cardiac activity even in case of emergency test termination due to medical complications.
Testing variability
As the system helps increase mobility, it also opens up more possibilities in choosing suitable exercises, including stair climbing and treadmill walking.
Risk assessment
The risk assessment tool uses the study results to automatically determine the risk of patient mortality and the occurrence of ischemic heart disease.
We continue to provide you with the latest news in the field of cardiology and monitoring methods. Stay connected and delve into the outstanding range of solutions which Norav Medical provides for your practical convenience. Join the growing family of our partners and see new horizons of ECG technology together with us.
References:
Hannun, A. Y., Rajpurkar, P., Haghpanahi, M., Tison, G. H., Bourn, C., Turakhia, M. P., & Ng, A. Y. (2019). Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nature medicine, 25(1), 65-69.
Scherz, W. D., Baun, J., Seepold, R., Madrid, N. M., & Ortega, J. A. (2020). A portable ECG for recording and flexible development of algorithms and stress detection. Procedia computer science, 176, 2886-2893.