Abstract: The present invention relates to an active medical device that uses non-linear filtering for reconstructing a surface electrocardiogram from an endocardial electrogram. At least one endocardial EGM electrogram signal is collected from of samples collected from at least one endocardial or epicardial derivation (71?, 72?, 73?), and at least one of a reconstructed surface electrocardiogram (ECG) signal through the processing of collected EGM samples by a transfer function (TF) of a neural network (60?). The neural network (60?) is a time-delay-type network that simultaneously processes said at least one endocardial EGM electrogram signal, formed by a first sequence of collected samples, and at least one delayed version of this EGM signal, formed by a second sequence of collected samples distinct from the first sequence collected samples. The neural network (60?) provides said reconstructed ECG signal from the EGM signal and its delayed version.

Abstract: The reconstruction of a surface electrocardiogram based upon an endocardial electrogram. This method includes: (a) acquisition (10) of a plurality of endocardial electrogram signals (EGM) through a plurality of endocardial leads defined based upon endocardial electrodes; (b) calculation (12), by combining the endocardial electrogram (EGM) signals acquired at step (a), of the corresponding endocardial vectogram (VGM); (c) angular rescaling (14) of the orthonormalized mark of the endocardial vectogram (VGM) with that of the surface vectocardiogram (VCG); (d) estimation (16), based upon the endocardial vectogram (VGM) calculated at step (b), of a reconstructed surface vectocardiogram (VCGreconstructed), and (e) calculation (18) of the surface electrocardiogram (ECG) corresponding to said reconstructed surface vectocardiogram (VCGreconstructed).

Abstract: The reconstruction of a surface electrocardiogram based upon an endocardial electrogram. This method includes: (a) acquisition (10) of a plurality of endocardial electrogram signals (EGM) through a plurality of endocardial leads defined based upon endocardial electrodes; (b) calculation (12), by combining the endocardial electrogram (EGM) signals acquired at step (a), of the corresponding endocardial vectogram (VGM); (c) angular resealing (14) of the orthonormalized mark of the endocardial vectogram (VGM) with that of the surface vectocardiogram (VCG); (d) estimation (16), based upon the endocardial vectogram (VGM) calculated at step (b), of a reconstructed surface vectocardiogram (VCGreconstructed), and (e) calculation (18) of the surface electrocardiogram (ECG) corresponding to said reconstructed surface vectocardiogram (VCGreconstructed).

Abstract: The present invention relates to an active medical device that uses non-linear filtering for reconstructing a surface electrocardiogram from an endocardial electrogram. At least one endocardial EGM electrogram signal is collected from of samples collected from at least one endocardial or epicardial derivation (71?, 72?, 73?), and at least one of a reconstructed surface electrocardiogram (ECG) signal through the processing of collected EGM samples by a transfer function (TF) of a neural network (60?). The neural network (60?) is a time-delay-type network that simultaneously processes said at least one endocardial EGM electrogram signal, formed by a first sequence of collected samples, and at least one delayed version of this EGM signal, formed by a second sequence of collected samples distinct from the first sequence collected samples. The neural network (60?) provides said reconstructed ECG signal from the EGM signal and its delayed version.

Abstract: A device for the analysis of an endocardiac signal of acceleration. The device preprocesses the acquired endocardiac acceleration (EA) signal by cutting the signal EA collected into sub-signals EA, each one have a duration of one cardiac cycle; separating the cut signals to isolate in each sub-signal EA at least one component EAx, associated with a major cardiac sound, and preferably into components EA1 and EA2 associated with the two major cardiac sounds S1 and S2; and performing a correlation on each component EA1 and EA2, to readjust each sub-signal in relation to a maximum of correlation, so as to deliver a readjusted component EA1 and a readjusted component EA2. The device further determines, starting from the isolated correlated components EA1 and EA2, a component average EA1 and a component average EA2, and to combine these components EA1 and average EA2 so as to produce an average global signal EA for one cycle.

Abstract: The reconstruction of a surface electrocardiogram based upon an endocardial electrogram. This method includes: (a) acquisition (10) of a plurality of endocardial electrogram signals (EGM) through a plurality of endocardial derivations defined based upon endocardial electrodes; (b) calculation (12), by combining the endocardial electrogram (EGM) signals acquired at step (a), of the corresponding endocardial vectogram (VGM); (c) angular resealing (14) of the orthonormated mark of the endocardial vectogram (VGM) with that of the surface vectocardiogram (VCG); (d) estimation (16), based upon the endocardial vectogram (VGM) calculated at step (b), of a reconstructed surface vectocardiogram (VCGreconstructed); and (e) calculation (18) of the surface electrocardiogram (ECG) corresponding to said reconstructed surface vectocardiogram (VCGreconstructed).

Abstract: The reconstruction of a surface electrocardiogram based upon an endocardial electrogram. This method includes: (a) acquisition (10) of a plurality of endocardial electrogram signals (EGM) through a plurality of endocardial derivations defined based upon endocardial electrodes; (b) calculation (12), by combining the endocardial electrogram (EGM) signals acquired at step (a), of the corresponding endocardial vectogram (VGM); (c) angular resealing (14) of the orthonormated mark of the endocardial vectogram (VGM) with that of the surface vectocardiogram (VCG); (d) estimation (16), based upon the endocardial vectogram (VGM) calculated at step (b), of a reconstructed surface vectocardiogram (VCGreconstructed), and (e) calculation (18) of the surface electrocardiogram (ECG) corresponding to said reconstructed surface vectocardiogram (VCGreconstructed).

Abstract: Disclosed is a method and system for providing constant critical AC electrical load with primary, secondary, and in some cases a tertiary source of power with higher reliability and lower operating and capital costs and lower emissions than the traditional utility supply, uninterruptible power supply (UPS), and battery primary power source, and diesel generator back-up systems that are predominately used today. Specifically, the disclosed system utilizes on-site power generation to provide primary power and includes full utility and UPS/DC storage back-up systems.