A new study from Cardiogram shows heart rate sensors you’re wearing already – like the Apple Watch, Android Wear, Garmin, or Fitbit – can detect early signs of diabetes.
Four times as many people have Type II diabetes today as 36 years ago, according to the World Health Organisation. In 1980, 108 million people were diagnosed with diabetes worldwide. By 2014, the figure was 422 million.
Researchers at Cardiogram and University of California, San Francisco validated the accuracy of DeepHeart, a deep neural network, in distinguishing between people with and without diabetes, achieving 85% accuracy on a large data set which included 200 million heart rate and step count measurements.
While there have been many attempts to build special-purpose glucose-sensing hardware to detect diabetes, Cardiogram said in the organisations’ blog that this is the first large-scale study showing that ordinary heart rate sensors—when paired with an artificial intelligence-based algorithm—can identify early signs of diabetes.
“By detecting diabetes earlier, we can help people live longer and healthier lives,” Brandon Ballinger, Cardiogram co-founder, wrote in the organisation’s blog.
Why can diabetes be detected from heart rate and step count data?
“Your heart is connected with your pancreas via the autonomic nervous system,” wrote Cardiogram co-founder Johnson Hsieh.
He added that as people develop the early stages of diabetes, their pattern of heart rate variability shifts. In 2015, the Framingham Heart Study showed that high resting heart rate and low heart rate variability predicts who will develop diabetes over a 12-year period (https://academic.oup.com/jcem/article/100/6/2443/2829673).
In 2005, the ARIC study showed that heart rate variability declines faster in diabetics than non-diabetics over a 9-year period (http://care.diabetesjournals.org/content/28/3/668.short).
Download the paper here: “DeepHeart: Semi Supervised Sequence Learning for Cardiovascular Risk Prediction” is available here