Name: Monitoring Heart-Rate Using Web-Cam
Description: This project deals with real-time monitoring of a person’s heartbeat using web-cam. It replaces the traditional machines used for measuring the heart-rate which not only limits the mobility of patients but also causes local skin problems and may aid the spread of contagious infections between patients.
Requirements:
To run the above cod e the requirements are:
Setup:
• Python 3.7
• Laptop with a webcam
Modules:
• Opencv
pip install opencv-python
pip install opencv-contrib-python
• datetime
pip install datetime
• Matplotlib
Pip install matplotlib
• Pytimeparse
Pip install pytimeparse
• Pylab
Pip install pylab
• Skimage
Pip install scikit-image
Run the project:
- Open cmd with the folder containing the project
- Python pulse.py
- Person’s face should be tracked by the webcam
The above commands will run the project. In order to smoothly execute the code a fluorescent light should be placed in front of the person’s face.
Input Sample:
• The webcam must track the person’s face perfectly using haarcascade frontal face detection.
• The green box is used to detect the person’s face.
• The blue box is used to detect the forehead (adjust your position according to the blue box in such a manner that forehead lies within the box)
• Color variation will be seen in the blue box representing the change in pixel intensity with each cardiac cycle
• If there are no color variations, then external luminous provided by the fluorescent light isn’t sufficient
• The person need to wait until 90 frames to get the heartrate
Output Sample:
Figure (a):
• This graph represents the change in ppg (Photoplethysmography) signals with time.
• There could be sudden increase or drop in the frequency due to external disturbance like light intensity.
• The graph also contains the person’s heart rate measured per minute.
Figure (b), (c):
• The figure b represents the variations of ppg signals in RGB channel
• The figure c represents the variations of ppg signals in LAB channel
• This figures are used to signify the variation of ppg signals in RGB and lab color space with motion artifacts of the person
Figure (d):
• This figure shows command prompt after closing all the graph windows.
• The cmd contains “Face not Found” for those frames whose face is not detected by haar-cascade algorithm.
• The frames in which the face is not detected are pruned
• The measured HeartRate is also displayed on the cmd .
References: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995145/
http://www.ep.liu.se/ecp/129/002/ecp16129002.pdf