Dynalets: A New Tool for Biological Signal Processing

The biological information coming from electro-physiologic signal sensors needs compression for an efficient medical use or for retaining only the pertinent explanatory information about the mechanisms at the origin of the recorded signal. When the signal is periodic in time and/or space, classical compression procedures like Fourier and wavelets transforms give good results concerning the compression rate, but provide in general no additional information about the interactions between the elements of the living system producing the studied signal. Here, we define a new transform called Dynalets based on Lienard differential equations susceptible to model the mechanism at the source of the signal and we propose to apply this new technique to real signals like ECG.