News: Try out VitalLens, my new free iOS app implementing a modern rPPG model based on AI. We also have an API with a Python Client which uses the same AI model. Find out more at https://www.rouast.com/vitallens and https://www.rouast.com/api.

This is a simple implementation of rPPG, a way to measure heart rate without skin contact. It uses a video recording or live feed of the face to analyse subtle changes in skin color.

Here's how it works:

• The face is detected and continuously tracked
• Signal series is obtained by determining the facial color in every frame
• Heart rate is estimated using frequency analysis and filtering of the series

If you are interested in the specifics, feel free to have a read of my publications on the topic:

• Remote Photoplethysmography: Evaluation of Contactless Heart Rate Measurement in an Information Systems Setting
• Using Contactless Heart Rate Measurements for Real-Time Assessment of Affective States
• Remote heart rate measurement using low-cost RGB face video: A technical literature review

See also my minimal JavaScript implementation and Browser Demo.

• Real-time rPPG in action
• Offline rPPG With physiological baseline measurements

The following libraries are required to run Heartbeat:

• OpenCV

They must be installed on the system such that headers and libraries are found on the compiler's standard search path.

For building a Makefile is available that works on macOS:

$ make

Alternative compilation for Ubuntu. Works with opencv 3.1:

$ g++ -std=c++11 Heartbeat.cpp opencv.cpp RPPG.cpp `pkg-config --cflags --libs opencv` -o Heartbeat

After building, the app can be run via

$ ./Heartbeat

Several command line arguments are available:

GPL-3.0