120 results about "R-R Interval" patented technology

An method for analyzing irreversible apneic coma (IAC) for determining the presence of irreversible apneic coma (IAC) by analyzing the heart rate variability of a brain traumatic patient, thereby providing a physician a reference index to determine whether brain death has occurred. This method includes, at first, recording an electrocardiogram (ECG) from a subject. Then, analyzing R-R interval in said electrocardiogram (ECG), and plotting said R-R interval into Poincaré plot, wherein the X coordinate in said Poincaré plot represents R-R interval(n), and n is a 1˜data number. Y coordinate in said Poincaré plot represents RR(n+1). And, finally, quantifying said Poincaré plot, and obtaining semi-major axis (SD1), semi-minor axis (SD2), and SD1 / SD2 of said Poincaré plot, as well as Poincaré plot area.

A signal indicative of cardiac contractions of a patient's heart is produced, as the patient's heart is paced using different sets of pacing interval parameters. Measures of pulse amplitude are obtained from the signal. Pacing interval optimization is performed based on the measures of pulse amplitude.

An assessment of sleep quality and sleep disordered breathing is determined from the cardiopulmonary coupling between two physiological data series. In an embodiment, an R-R interval series is derived from an electrocardiogram (ECG) signal. The normal beats from the R-R interval series are extracted to produce a normal-to-normal (NN) interval series. The amplitude variations in the QRS complex are used to extract to a surrogate respiration signal (i.e., ECG-derived respiration (EDR)) that is associated with the NN interval series. The two series are corrected to remove outliers, and resampled. The cross-spectral power and coherence of the two resampled signals are calculated over a plurality of coherence windows. For each coherence window, the product of the coherence and cross-spectral power is used to calculate coherent cross power. Using the appropriate thresholds for the coherent cross power, the proportion of sleep spent in CAP, non-CAP, and wake and / or REM are determined.

Ventricular stroke volume variation (SVV) is estimated as a function of the standard deviation of arterial blood pressure value measured over each of at least two cardiac cycles, preferably over each of the cardiac cycles in a computation interval covering a full respiratory cycle. In one embodiment, maximum and minimum standard deviation values are determined over the computation interval. SVV is then estimated proportional to the ratio of the difference between the maximum and minimum standard deviation values and the mean of the standard deviation values. In another embodiment, SVV is then estimated proportional to the ratio of the standard deviation of the standard deviation values and the mean standard deviation over the entire computation interval. A pre-processing arrangement for improving reliability of estimates of more general cardiac or hemodynamic parameters is also disclosed and involves smoothing with an approximating function, and sampling and low-pass filtering at an adjustable rate.

Methods and devices for establishing and using baseline for cardiac pacing response detection are described. A baseline amplitude of the cardiac signal may be established using data acquired in an evaluation interval prior to the delivery of the pacing pulse. An amplitude of the cardiac signal following delivery of the pacing pulse may be referenced using the baseline amplitude. An evoked response from the pacing pulse is detected using the referenced cardiac signal amplitude.

The disclosure provides methods and apparatus of left ventricular pacing including automated adjustment of a atrio-ventricular (AV) pacing delay interval and intrinsic AV nodal conduction testing. It includes—upon expiration or reset of a programmable AV Evaluation Interval (AVEI)—performing the following: temporarily increasing a paced AV interval and a sensed AV interval and testing for adequate AV conduction and measuring an intrinsic atrio-ventricular (PR) interval for a right ventricular (RV) chamber. Thus, in the event that the AV conduction test reveals a physiologically acceptable intrinsic PR interval then storing the physiologically acceptable PR interval in a memory structure (e.g., a median P-R from one or more cardiac cycles). In the event that the AV conduction test reveals an AV conduction block condition or if unacceptably long PR intervals are revealed then a pacing mode-switch to a bi-ventricular (Bi-V) pacing mode occurs and the magnitude of the AVEI is increased.

A system and automated method for assessing ventricular synchrony in ambulatory patients is provided including at least one mechanical sensor (e.g., accelerometer, tensiometric sensor, force transducer, and the like) operatively coupled to a first myocardial location in order to measure a wall motion signal of a first chamber, and a second mechanical sensor operatively coupled to a second myocardial location in order to measure a wall motion signal of a second chamber. The wall motion signals are processed in order to identify the time at which a fiducial (e.g., an inflection point, a threshold crossing, a maximum amplitude, etc.) occurs for each respective signal. The temporal separation between the fiducial points on each respective signal is measured as a metric of ventricular synchrony and can be optionally utilized to adjust pacing therapy timing to improve synchrony.

The present invention is a cardiac rhythm-monitoring device, which allows patients to perform a preliminary screening for supraventricular arrhythmia. The device detects beat-to-beat heart rhythms (i.e. the R-R interval between individual heart beats) and performs a screening test to determine if there are indications of arrhythmia. The test looks for variance in the R-R interval that is outside of the normal range, either using a pre-constructed chart based upon general population studies to determine the normal range of variance or using normal distribution analysis of the patient's own heart rhythm to determine the normal range of variance for determining irregular heartbeats, and if there are multiple irregularities within the sensed time frame, the patient is warned of potential supraventricular arrhythmia. By sensing both electrical impulses form the heart and mechanical responses to the heartbeat, the device may augment its analysis.

A technique for comparing pressure oscillations obtained during a blood pressure determination wherein two or more sets of matching criteria may be employed. The set of matching criteria to be employed is determined based on the heart rate variability or the presence of heart beat irregularities or arrhythmias as determined by an independent heart monitor, such as an ECG. The selected set of matching criteria may then be employed in determining the acceptability of the time interval between two oscillations and the equivalence of the two oscillations based upon one or more oscillation characteristics, such as peak amplitude. In this manner, non-consecutive oscillations may be matched and used in determining blood pressure.

The present invention is a cardiac rhythm-monitoring device, which allows patients to perform a preliminary screening for supraventricular arrhythmia. The device detects beat-to-beat heart rhythms (i.e. the R-R interval between individual heart beats) and performs a screening test to determine if there are indications of arrhythmia. The test looks for variance in the R-R interval that is outside of the normal range, either using a pre-constructed chart based upon general population studies to determine the normal range of variance or using normal distribution analysis of the patient's own heart rhythm to determine the normal range of variance for determining irregular heartbeats, and if there are multiple irregularities within the sensed time frame, the patient is warned of potential supraventricular arrhythmia. By sensing both electrical impulses form the heart and mechanical responses to the heartbeat, the device may augment its analysis.

An assessment of sleep quality and sleep disordered breathing is determined from cardiopulmonary coupling between two physiological data series. An R-R interval series is derived from an electrocardiogram (ECG) signal. The normal beats from the R-R interval series are extracted to produce a normal-to-normal interval series. The amplitude variations in the QRS complex are used to extract a surrogate respiration signal (i.e., ECG-derived respiration) associated with the NN interval series. The two series are corrected to remove outliers, and resampled. The cross-spectral power and coherence of the two resampled signals are calculated over a plurality of coherence windows. For each coherence window, the product of the coherence and cross-spectral power is used to calculate coherent cross-power. Using the appropriate thresholds for the coherent cross-power, the proportion of sleep spent in CAP, non-CAP, and wake and / or REM are determined. Coherent cross-power can be applied to differentiate obstructive from non-obstructive disease, and admixtures of the same.

A method of determining sleep stages from signals of electrical activity recorded of a chest of a sleeping subject, the signals being measured over a plurality of epochs. The method comprising: (a) extracting a series of cardiac R-R intervals from the signals and obtaining a time-frequency decomposition from the series of cardiac R-R intervals; (b) using the time-frequency decomposition to determine at least one Slow-Wave-Sleep (SWS) period and at least one Non-SWS (NSWS) period; (c) from the at least one NSWS period, determining at least one sleep-onset (SO) period and a plurality of non-sleep periods; (d) extracting a plurality of electromyogram (EMG) parameters from a portion of the signals, the portion corresponds to a NSWS period other than the at least one SO period and other than the plurality of non-sleep period; (e) using the plurality of EMG parameters to determine at least one REM period thereby also to obtain also at least one light-sleep (LS) period defined as a NSWS period other than the SO periods, other than the non-sleep periods and other than the REM periods; thereby determining the sleep stages of the sleeping subject.

The method and system includes detecting atrial fibrillation in a patient by monitoring the blood oxygen saturation level over a period of time. The method and system produces a plethysmographic waveform from the monitored blood oxygen saturation level and analyzes the plethysmographic waveform and detected intervals and determines whether the patient is in atrial fibrillation. The method and system is preferably implemented in a software application and may be configured to report to the user on the current state of atrial fibrillation (AFIB) and a current trend.