remotebiosensing/rppg
Benchmark Framework for fair evaluation of rPPG
This framework helps researchers and engineers fairly compare different algorithms for measuring vital signs like heart rate and continuous blood pressure from video, without physical contact. You input video data, and the system outputs evaluated performance metrics for various rPPG and CNIBP models, allowing you to select the most accurate method for your specific application. It's designed for professionals working on remote health monitoring and contactless physiological measurement.
315 stars.
Use this if you need to rigorously evaluate and benchmark different deep learning models for remote photoplethysmography (rPPG) and continuous non-invasive blood pressure (CNIBP) measurement using video data.
Not ideal if you are looking for a ready-to-use application for end-user health monitoring, as this is a research and development tool.
Stars
315
Forks
39
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 09, 2025
Commits (30d)
0
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