/Heart-rate-measurement-using-camera

real time application to measure heart rate

Primary LanguagePythonApache License 2.0Apache-2.0

Heart-rate-measurement-using-camera

Alt text

Abstract

  • Heart Rate (HR) is one of the most important Physiological parameter and a vital indicator of people‘s physiological state
  • A non-contact based system to measure Heart Rate: real-time application using camera
  • Principal: extract heart rate information from facial skin color variation caused by blood circulation
  • Application: monitoring drivers‘ physiological state

Methods

  • Detect face, align and get ROI using facial landmarks
  • Apply band pass filter with fl = 0.8 Hz and fh = 3 Hz, which are 48 and 180 bpm respectively
  • Average color value of ROI in each frame is calculate pushed to a data buffer which is 150 in length
  • FFT the data buffer. The highest peak is Heart rate
  • Amplify color to make the color variation visible

Requirements

  • numpy, opencv, dlib, imutils, scipy, PyQt4
  • Download and put file "shape_predictor_68_face_landmarks.dat" in the project folder

Implementation

  • Install all needed packages
  • Run GUI.py, appplication can run on either camera or video mode
python GUI.py
  • In case of plotting graphs, run "graph_plot.py"
  • For the Eulerian Video Magnification implementation, run "amplify_color.py"

Results

  • Data from a specialized device, Compact 5 medical Econet, is used for the ground truth. In certain circumstances, the Heart rate values measured using the application and the device are the same

Reference

  • Real Time Heart Rate Monitoring From Facial RGB Color Video Using Webcam by H. Rahman, M.U. Ahmed, S. Begum, P. Funk
  • Remote Monitoring of Heart Rate using Multispectral Imaging in Group 2, 18-551, Spring 2015 by Michael Kellman Carnegie (Mellon University), Sophia Zikanova (Carnegie Mellon University) and Bryan Phipps (Carnegie Mellon University)
  • Non-contact, automated cardiac pulse measurements using video imaging and blind source separation by Ming-Zher Poh, Daniel J. McDuff, and Rosalind W. Picard
  • Camera-based Heart Rate Monitoring by Janus Nørtoft Jensen and Morten Hannemose
  • Graphs plotting is based on https://github.com/thearn/webcam-pulse-detector
  • https://www.pyimagesearch.com/2017/04/03/facial-landmarks-dlib-opencv-python/

Note

  • Application can only detect HR for 1 people at a time
  • Sudden change can cause incorrect HR calculation. In the most case, HR can be correctly detected after 10 seconds being stable infront of the camera
  • This github project is for study purpose only. For other purposes, please contact me at khanhhanguyen2310@gmail.com

UPDATE

  • 6/11:

    • Use pyqtgraph for plotting graph
    • Add age and gender detection Alt text

  • 17/11:

    • Add find 5 facial landmarks feature. Download and put shape_predictor_68_face_landmarks.dat in the project folder.

  • 23/11: Add classes and tests in new_update folder

    • face_utilities: functions to work with faces in a frame
    • test_face_utilities.py: test the functions in face_utilities.py
    • signal_processing.py: functions for signal processing.
    • test_signal_processing.py: test the functions in signal_processing.py combined with face_utilities.py. Also renders a txt file which has HR over time (of a video).