Signal recovery in imaging photoplethysmography.

Imaging photoplethysmography is an emerging technique for the extraction of biometric information from people using video recordings. The focus is on extracting the cardiac heart rate of the subject by analysing the luminance of the colour video signal and identifying periodic components. Advanced signal processing is needed to recover the information required. In this paper, independent component analysis (ICA), principal component analysis, auto- and cross-correlation are investigated and compared with respect to their effectiveness in extracting the relevant information from video recordings. Results obtained are compared with those recorded by a modern commercial finger pulse oximeter. It is found that ICA produces the most consistent results.