Breathing Evaluation Using Video and Other Signals Project
Overview
Exploring novel approaches to assess breathing patterns by integrating video-based analysis with other sensor signals.
Background
Traditional respiratory monitoring often relies on sensors placed on the body. Video-based methods, combined with signal processing from various sources, can offer some advantages.
Aim
To develop techniques that use video streams and supplemental signals to accurately measure and evaluate breathing patterns without direct contact.
Methods
Employing computer vision algorithms, optical flow, and machine learning to extract respiratory information from video, while integrating data from other non-invasive sensors for improved reliability.
Results
Initial tests indicate that combining video analysis with additional signals can enhance breathing pattern detection, providing a contactless alternative for respiratory monitoring
Resources