Non-invasive in vivo Raman spectroscopy of the skin for diabetes screening Conference Paper uri icon


  • This work describes the application of portable Raman spectroscopy coupled with Artificial Neural Networks (ANN), to discern between diabetic patients and healthy controls, with a high degree of accuracy (Acc=89.7±6.6%25). This technique is relatively low-cost, simple and comfortable for the patient, yielding rapid diagnosis. These features make our method a promising screening tool for identifying type 2 diabetes mellitus (DM2) in a non-invasive and automated fashion. © 2017 IEEE.

publication date

  • 2017-01-01