Using artificial intelligence to detect hypoglycaemic events via wearable sensors

Dr Leandro Pecchia

Article Highlights

Tracking sugar in the blood is crucial for both healthy individuals and diabetic patients. Current methods to measure glucose requires needles and repeated fingerpricks over the day. Fingerpricks can often be painful, deterring patient compliance
A new technique developed by researchers at the University of Warwick uses the latest findings of Artificial Intelligence to detect hypoglycaemic events from raw ECG signals, via wearable sensors
The technology works with an 82% reliability, and could replace the need for invasive finger-prick testing with a needle, which could be particularly useful for paediatric age patients
“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.”
“Our approach enable personalised tuning of detection algorithms and emphasize how hypoglycaemic events affect ECG in individuals. 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.”

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