Non invasive and quite easy to measure signals like the multi-derivation electrocardiograms (ECG) can be used for the diagnostic of many cardiac and autonomic nervous system disease states.
The Scilab module for cardiovascular wave analysis is a collection of more than 90 functions for reading, visualizing and analysis of cardiovascular wave such as multi derivation ECG, blood pressure, breathing…
Several input data formats, the large files generated by long duration records such as those given by the cardiac holter devices can be managed.
In addition to the basic Scilab signal processing tools, specific functions are provided for the signal pretreatment like 50Hz removal, ECG baseline wander removal, sub-sampling,…
Powerful detection algorithms which allow localization of QRS complex events like the Q, R, S, T peaks, as well as the beginning and the end of the waves are provided. The duration, amplitude, and morphology of the QRS complex are useful for the diagnosis of many cardiac disease states.
Algorithms based on complex demodulation, time frequency analysis or multi-channel non-stationary signal analysis are provided for analysing the behaviour of the baroreflex mechanism from the RR variations with respect to arious signals like the systolic or diastolic blood pressure, the tidal volume respiratory. The baroreflex mechanisms driven by the autonomic nervous system provides a rapid feedback loop which aims to regulate the blood pressure.
A set of specific functions is provided for the visualization of the ECG and the location of the QRS events with interactive capabilities for long signals.
The key algorithms of this module have been developed and validated by the SISYPHE INRIA team in the context of clinical studies.
Biomedical, cardiovascular, ECG, detection, baroreflex
 Rapport de recherche INRIA RR-4427:Short term control of the cardiovascular system: modelling and signal analysis, Alessandro Monti, Claire Médigue, Michel Sorine,2002
 Q. Zhang, A. Illanes Manriquez, C. Médigue, Y. Papelier, and M.Sorine. An algorithm for robust and efficient location of T-wave ends in electrocardiograms. IEEE Trans. on Biomedical Engineering, 53(12):2544-2552, 2006.
 Instantaneous parameter estimation in cardiovascular time series by harmonic and time-frequency analysis, Alessandro Monti , Claire Médigue , Mangin Laurence, IEEE Trans Biomed Eng. 2002 Dec;49(12 Pt 2):1547-56.