AI monitors glucose levels with ECG data

Patients can now use AI to monitor their glucose levels with off-the-shelf, noninvasive wearable sensors, according to a new study published in Scientific Reports.

One significant advantage of this method, the authors explained, is that it uses ECG data—this means patients can stay informed about their health without a needing a “fingerpick test.”

“Fingerpicks are never pleasant and in some circumstances are particularly cumbersome,” Leandro Pecchia, PhD, from the school of engineering at the University of Warwick, said in a prepared statement. “Taking fingerpick during the night certainly is unpleasant, especially for patients in pediatric age.”

Pecchia and colleagues developed the technique, which can even monitor’s a patient glucose levels as they sleep, and then tested its effectiveness through two pilot studies. Overall, the method achieved an average sensitivity and specificity of 82%, which is comparable to the performance of currently available continuous glucose monitors. One reason for the team’s success is that their AI algorithm was trained using data from each individual subject, displaying the potential of personalized patient care.

“Our approach enable personalized tuning of detection algorithms and emphasize how hypoglycemic events affect ECG in individuals,” Pecchia said in the same statement. “Basing on this information, clinicians can adapt the therapy to each individual. Clearly more clinical research is required to confirm these results in wider populations. This is why we are looking for partners.”