title: Dynalets: a new method for modelling and compressing biological signals. Applications to physiological and molecular signals.
abstract: The biological information coming from electrophysiologic sensors like ECG, pulse sensor or from molecular signal devices like NMR spectrometry has to be visualized and manipulated in a compressed way for an efficient medical use by clinicians, if stored in scientific data bases or in personalized patient records repositories. Here, we define a new transform called Dynalet based on Liénard ordinary differential equations susceptible to model the mechanism at the source of the studied signal, and we propose to apply this new technique first to the modelling and compression of real biological periodic signals like ECG and pulse rhythm. We consider that the cardiovascular activity results from the summation of cellular oscillators located in the cardiac sinus node and we show that, as a result, the van der Pol oscillator (a particular Liénard system) fits well the ECG signal and the pulse signal. The reconstruction of the original signal (pulse or ECG) using Dynalet transform is then compared with that of Fourier, counting the number of parameters to be set for obtaining an expected signal-to-noise ratio. Then, we apply the Dynalet transform to the modelling and compression of molecular spectra obtained by protein NMR spectroscopy. The reconstruction of the original signal (peak) using Dynalet transform is again compared with that of Fourier. After reconstructing visually the peak, we propose to periodize the signal and give it to hear, the whole process being called the protein "stethoscope".
authors.affiliation: Université Joseph-Fourier, Grenoble, AGIM CNRS FRE 3405, Faculté de médecine, 38700 La Tronche, France. Electronic address: Jacques.Demongeot@agim.eu.
authors.forename: Jacques
authors.initials: J
authors.lastname: Demongeot
authors.affiliation: Université Joseph-Fourier, Grenoble, AGIM CNRS FRE 3405, Faculté de médecine, 38700 La Tronche, France.
authors.forename: Olivier
authors.initials: O
authors.lastname: Hansen
authors.affiliation: Université Joseph-Fourier, Grenoble, AGIM CNRS FRE 3405, Faculté de médecine, 38700 La Tronche, France.
authors.forename: Ali
authors.initials: A
authors.lastname: Hamie
authors.affiliation: Université Joseph-Fourier, Grenoble, AGIM CNRS FRE 3405, Faculté de médecine, 38700 La Tronche, France.
authors.forename: Céline
authors.initials: C
authors.lastname: Franco
authors.affiliation: King's College, Strand, London WC2R 2LS, United Kingdom.
authors.forename: Brian
authors.initials: B
authors.lastname: Sutton
authors.affiliation: Université Joseph-Fourier, Grenoble, AGIM CNRS FRE 3405, Faculté de médecine, 38700 La Tronche, France; King's College, Strand, London WC2R 2LS, United Kingdom.
authors.forename: Elie-Paul
authors.initials: EP
authors.lastname: Cohen
mesh_terms: D002320:Cardiovascular Physiological Phenomena; D016208:Databases, Factual; D004562:Electrocardiography; D005583:Fourier Analysis; D055991:Health Records, Personal; D006801:Humans; D009682:Magnetic Resonance Spectroscopy; D055641:Mathematical Concepts; D008962:Models, Theoretical; D063177:Pulse Wave Analysis; D012815:Signal Processing, Computer-Assisted
keywords: Compression des signaux ECG et pouls; Dynalet transform; Fourier transform; Heart and pulse signals compression; Protein “stethoscope”; Signal processing; Traitement du signal; Transformation Dynalet; Transformation de Fourier; « Stéthoscope » protéique