Author Interviews, Diabetes, Technology, UCSF / 12.03.2019
Smartphone App Will Be Able to Predict Diabetes
MedicalResearch.com Interview with:
Robert Avram MD MSc
Division of Cardiology
University of California, San Francisco
MedicalResearch.com: What is the background for this study? Would you briefly describe what is meant by Photoplethysmography?
While analyzing the heart rate data as collected using smartphones apps in the Health-eHeart study, we noticed that diabetic patients had, on average, a higher ‘free-living’ heart rate than non-diabetic patients when adjusted from multiple factors. This pushed us to analyze the signal to see if there were other features that would help differentiate diabetes patients from non-diabetes patients. By identifying these features, we saw a huge opportunity to develop a screening tool for diabetes using deep learning and a smartphone camera and flash, in order to classify patients as having prevalent diabetes/no-diabetes.
Photoplethysmography is the technique of measuring the difference in light absorption by the skin in order to detect blood volume changes in the microvasculature. Most modern mobile devices, including smartphones and many fitness trackers (Apple Wathc, FitBit), have the ability to acquire PPG waveforms, providing a unique opportunity to detect diabetes-related vascular changes at population-scale. (more…)