ECG is very inexpensive, said senior study author Partho Sengupta, Henry Rutgers professor and chief of cardiology at Rutgers Robert Wood Johnson Medical School and the chief of cardiology at Robert Wood Johnson University Hospital, an RWJBarnabas Health facility. It's even present in the Apple Watch, so millions use it constantly. An echocardiogram is about 5 to 10 times more expensive than an ECG because it requires an expert moving an ultrasound device over the patient’s chest for a significant period.

The patent-pending technology uses generative AI to assess the speed of cardiac tissue during a heartbeat using electrical signals from ECG. Then, it converts the signals to develop a speed waveform that looks exactly like the waves conventionally measured with Doppler ultrasound imaging during echocardiography. These types of signals enable doctors to see how well the heart is pumping and relaxing during a heartbeat. This innovation addresses a critical healthcare gap: finding a way to detect heart dysfunction early with cheap and widely available tools like ECG and referring the right patients to specialists for more expensive imaging tests.

The researchers used generative adversarial networks (GANs) to train AI models that generate synthetic heart motion waveforms from electrical signals. In rigorous testing at multiple clinical sites in the United States and Canada, the technology demonstrated high accuracy in detecting both diastolic dysfunction (problems with the heart relaxing) and systolic dysfunction (problems with the heart contracting).

When risk factors like high blood pressure, diabetes or coronary artery disease start affecting the heart muscle, conventional measurements in ECG-detectable changes come very late, Sengupta said. The synthetic TDI can detect subtle longitudinal changes in heart function long before the pumping fraction decreases. The novelty is not just relying on a change in pumping fraction – also referred to as ejection fraction – but more subtle changes in heart tissue motion.

Source: https://www.rutgers.edu/news/artificial-intelligence-recreates-motion-beating-heart-using-surface-electrical-recordings