SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network.

Journal: AMIA ... Annual Symposium proceedings. AMIA Symposium
Published Date:

Abstract

Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-invasively. We recorded 10 second-300 frame fingertip videos using a smartphone in 75 adults. Red, green, and blue pixel intensities were estimated for each of 100 area blocks in each frame and the patterns across the 300 frames were described. ANN was then used to develop a model using the extracted video features to predict hemoglobin levels. In our study sample, with patients 20-56 years of age, and gold standard hemoglobin levels of 7.6 to 13.5 g/dL., we observed a 0.93 rank order of correlation between model and gold standard hemoglobin levels. Moreover, we identified specific regions of interest in the video images which reduced the required feature space.

Authors

  • Md Kamrul Hasan
    Marquette University, Milwaukee, WI, USA.
  • Md Munirul Haque
    Purdue University, West Lafayette, IN, USA.
  • Riddhiman Adib
    Marquette University, Milwaukee, WI, USA.
  • Jannatul F Tumpa
    Marquette University, Milwaukee, WI, USA.
  • Azima Begum
    Dhaka Medical College and Hospital, Bangladesh.
  • Richard R Love
    Marquette University, Milwaukee, WI, USA.
  • Young L Kim
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA eowere@mu.ac.ke martin.c.were@vumc.org youngkim@purdue.edu.
  • I Ahamed Sheikh
    Marquette University, Milwaukee, WI, USA.