AI tracks blood sugar without fingerprick using ECG

News

An AI system developed at Warwick University can detect low glucose levels using ECG data without the need for an invasive fingerprick test.

Existing Continuous Glucose Monitors (CGM) measure glucose in interstitial fluid using an invasive sensor with a small needle, which in turn sends data and alarms to a display device. But many patients find this fingerprick testing painful and this can result in low levels of compliance, particularly for children. Using wearable ECG sensors and AI, the Warwick team was able to detect hypoglycaemic events with 82 per cent accuracy, which they claim is comparable to current GCM performance.

How AI is powering a revolution in medical diagnostics

Infrared and AI combine for new brain tumour blood test

"Fingerpicks are never pleasant and in some circumstances are particularly cumbersome,” said Dr Leandro Pecchia, from Warwick’s School of Engineering. “Taking fingerpicks during the night certainly is unpleasant, especially for patients in paediatric age.

"Our innovation consisted in using artificial intelligence for automatic detecting hypoglycaemia via few ECG beats. This is relevant because ECG can be detected in any circumstance, including sleeping."

Register now to continue reading

Thanks for visiting The Engineer. You’ve now reached your monthly limit of news stories. Register for free to unlock unlimited access to all of our news coverage, as well as premium content including opinion, in-depth features and special reports.  

Benefits of registering

  • In-depth insights and coverage of key emerging trends

  • Unrestricted access to special reports throughout the year

  • Daily technology news delivered straight to your inbox

Register
Or continue by

Signing in with your registered email address