Can ICA be applied, when the number of mixture signal is less than number of source signal?

I am referring to the the following paper : Non-contact, automated cardiac pulse measurements using video imaging and blind source separation

In the above article, the authors are able to extract cardiac pulse signal out from RGB components. I try to visualize the process as follow.

R' = R + cardiac pulse
G' = G + cardiac pulse
B' = B + cardiac pulse

R', G' and B' are the colour components observed by camera. R, G, B are the colour components for a person, by assuming that he doesn't have any cardiac pulse.

It seems that we will be having 4 sources (R, G, B, Cardiac pulse). We are now trying to obtain 1 of the 4 sources (Cardiac pulse) from 3 mixture signals (R', G', B'), by using ICA.

Does it make sense? Am I missing some techniques? Or, am I making a wrong assumption on the process?

Answer

You might also want to consider Principal Component Analysis (PCA) or an extension of it known as Independent Subspace Analysis which is PCA followed by ICA. These techniques work very well for extracting pitch stationary signals from a single observation signal. I'm an audio specialist but have discussed biomedical signals with colleagues in the past and from recollection cardiac pulses from a single observation are pretty well characterised and thus would be suitable sources for extraction using ISA. I have used it to great avail to separate drums from full musical polyphonies.