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Showing papers by "Reinhold Orglmeister published in 2003"


01 Jan 2003
TL;DR: A novel technique for the detection of QRS complexes in electrocardiographic signals that is based on a feature obtained by counting the number of zero crossings per segment, which provides a computationally efficient solution to the QRS detection problem.
Abstract: Summary There is a novel technique for the detection of QRS complexes in electrocardiographic signals that is based on a feature obtained by counting the number of zero crossings per segment. It is well-known that zero crossing methods are robust against noise and are particularly useful for finite precision arithmetic. The new detection method inherits this robustness and provides a high degree of detection performance even in cases of very noisy electrocardiographic signals. Furthermore, due to the simplicity of detecting and counting zero crossings, the proposed technique provides a computationally efficient solution to the QRS detection problem. The excellent performance of the algorithm is confirmed by a sensitivity of 99.70% (277 false negatives) and a positive predictivity of 99.57% (390 false positives) against the MIT-BIH arrhythmia database.

99 citations


Proceedings ArticleDOI
06 Apr 2003
TL;DR: A robust independent component analysis (ICA) algorithm for blind separation of convolved mixtures of speech signals is introduced, based on two parallel frequency dependent beamforming stages, each of which cancels the signal from one interfering source by frequency dependent null-beamforming.
Abstract: A robust independent component analysis (ICA) algorithm for blind separation of convolved mixtures of speech signals is introduced. It is based on two parallel frequency dependent beamforming stages, each of which cancels the signal from one interfering source by frequency dependent null-beamforming. The zero-directions of the beamforming stages are optimized to yield maximally independent outputs, which is achieved via second and higher order statistics. Optimization is carried out in the frequency domain for each frequency band separately, so that phase distortions caused by the room impulse responses are compensated. In contrast to other frequency domain source separation algorithms, this structure does not suffer from permutation of frequency bands, while retaining the major advantage of blind methods, that do not require an external estimate of the direction of arrival (DOA).

22 citations


Patent
18 Mar 2003
TL;DR: In this article, a null-beamforming-analyse auf Basis eines Delay-and-Sum Verfahrens analysiert, um entmischte frequenzabhangige Ausgangssignale Yl(ω) bzw X2(ω), zu bilden, die anschliesend in ausgefuhrten Null-Beamforming analysis was analyzed, wobei Einfallswinkel φ1 and φ2 were transformiert.
Abstract: Die Erfindung betrifft ein Verfahren und eine Vorrichtung zum Entmischen von akustischen Signalen Bei dem werden mit Hilfe von wenigstens zwei akustischen Sensoren M1 und M2 mindestens zwei zeitabhangige akustische Mischsignale x1(t) und x2(t) erfast, die jeweils gemischte Signalanteile zeitabhangiger akustischer Quellsignale sl(t) und s2(t) von akustischen Signalquellen Q1 und Q2 umfassen Die akustischen Mischsignale xl(t) und x2(t) werden zum Bilden von frequenzabhangigen Mischsignalen X1(ω) und X2(ω) mit Hilfe einer Verarbeitungseinrichtung in den Frequenzbereich transformiert werden Mit Hilfe der Verarbeitungseinrichtung werden die frequenzabhangigen Mischsignale X1(ω) und X2(ω) mittels einer im Frequenzbereich ausgefuhrten Null-Beamforming-Analyse auf Basis eines Delay-and-Sum Verfahrens analysiert, um entmischte frequenzabhangige Ausgangssignale Yl(ω) und Y2(ω) zu bilden, die anschliesend in entmischte zeitabhangige Ausgangssignale yl(t) und y2(t) transformiert werden, wobei Einfallswinkel φ1 und φ2 der aus den zeitabhangigen akustischen Mischsignalen xl(t) und x2(t) abgeleiteten, frequenzabhangigen Mischsignale X1(ω) bzw X2(ω) bei der Null-Beamforming-Analyse auf Basis des Delay-and-Sum-Verfahrens als frequenzabhangige Einfallswinkel (φ1(ωk) und (φ2(ωk) fur mehrere Frequenzbander ωk (k = 1, 2, ) optimiert werden