Abstract: A cardiac-activity based prediction of a rapid drop in a patient's blood pressure during extracorporeal blood treatment is disclosed. A proposed alarm apparatus includes a primary beat morphology analysis unit bank of secondary analysis units and an alarm generating unit. The primary beat morphology analysis unit discriminates heart beats in a received basic electrocardiogram signal, classifies each beat into one out of at least two different beat categories, and associates each segment of the signal with relevant event-type data. The event-type data and the basic electrocardiogram signal together form an enhanced electrocardiogram signal, based upon which the primary beat morphology analysis unit determines whether one or more secondary signal analyses should be performed.

Abstract: The invention relates to prediction of a rapid symptomatic drop in a subject's blood pressure, e.g. during a medical treatment or when operating an aircraft. To this aim, a pulse shape parameter (Pps) with respect to a peripheral body part (105) of the subject (P) is registered by means of a pulse oximetry instrument (110) adapted to detect light response variations in blood vessels. An initial pulse magnitude measure is calculated based on a pulse shape parameter (Pps) received at a first instance. During a measurement period subsequent to the first instance, a respective pulse magnitude measure is calculated based on each of a number of received pulse shape parameters (Pps). It is further investigated, for each pulse magnitude measure in the measurement period, whether or not the measure fulfills a decision criterion relative to the initial pulse magnitude measure. An alarm triggering signal (?) is generated if the decision criterion is found to be fulfilled.

Abstract: The invention relates to cardiac-activity based prediction of a rapid drop in a patient's blood pressure during hemodialysis. A proposed alarm apparatus includes an input interface, primary and secondary analysis units and an alarm-generating unit. An electrocardiogram signal (HECG) of the patient is received via the input interface by the primary analysis unit, which in response thereto produces a heart-rate-variability signal (PHRV). The secondary analysis unit determines an intensity of ectopic beats (PEBC) based on the electrocardiogram signal (HECG). The alarm-generating unit investigates whether the intensity of ectopic beats (PEBC) is relatively low or relatively high. In case of a relatively low intensity, the unit triggers an alarm signal (?) indicative of an estimated rapid blood pressure decrease if the heart-rate-variability signal (PHRV) fulfills a first alarm criterion.

Abstract: An apparatus for detecting cardiac events in electrograms has a feature extraction unit that derives features of the cardiac events for discriminating among different types of cardiac events. A clustering unit groups cardiac events with similar features into respective clusters defined by predetermined cluster features. The feature extraction unit determines a feature vector describing waveform characteristics of cardiac events in the electrogram by a wavelet transform. The clustering unit determines the distance between the feature vector and corresponding cluster feature vectors in order to assign the cardiac event in question to that cluster which results in a minimum distance, providing that the minimum distance is less than a predetermined threshold value. A heart stimulator provided with such a cardiac event detecting apparatus detects the occurrence of an arrhythmia and appropriately controls a pulse stimulator to treat the arrhythmia.

Abstract: In a method of and apparatus for deriving indices characterizing atrial arrhythmias, a temporally isolated portion of a digital representation of a time-domain electrical signal originating from the atria of a patient is frequency analyzed to provide a corresponding frequency spectrum. The obtained frequency spectrum is compared with a template frequency spectrum, selectively adapted dependent on previously obtained frequency spectra from different temporally isolated portions, to determine a frequency shift value and an amplitude value that optimize a correlation between the two spectra. An output representing the two determined values is used, possibly together with parameters describing the template frequency spectrum, to classify an atrial arrhythmia manifest in the digital representation.

Abstract: A detector for detecting a cardiac event in an IEGM has a bank of digital filters composed of at least two filters with substantially different impulse responses corresponding to different properties of the cardiac event. The filters respectively filter different portions of the IEGM and respectively emit a value per time unit corresponding to the morphological resemblance between the IEGM and the finite impulse response. An analyzing unit combines these output values from the filters in a predetermined manner for comparison with predetermined detection criteria.

Abstract: In a method for enhancing the signal-to-noise ratio of ECG signals, A/D-converted signals from a number of cardiac cycles are time-synchronized to form a signal ensemble, and the correlation between the signals in the ensemble is determined in time intervals, comprising at least two samples, during at least a part of the cardiac cycles. A device for enhancing the signal-to-noise ratio of ECG signals, includes circuitry for recording, A/D-converting and other processing of the ECG signals. A synchronization unit is arranged to time-synchronize the signals from a plurality of cardiac cycles to form a signal ensemble, and a calculator unit controlled by a window unit determines the correlation between the signals in the ensemble in time intervals, comprising at least two samples, during at least a part of the cardiac cycles.

Abstract: In a method and apparatus for processing ECG signals for the purpose of detecting low-amplitude signal structures hidden in noise in the ECG signal, the ECG signals, number of cardiac cycles are analog-to-digital converted, and QRS complexes in the converted signals are detected. The signals from at least two cardiac cycles are cross-correlated, and the correlation between these signals in time intervals which comprise at least the time intervals of the two samples is determined. An output quantity representing the degree of correlation is thus obtained, the magnitude of this quantity designating the amplitude of the signal structure in question. This magnitude can then be analyzed to determine if, and where in the signal, the signal structure arises.